A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints
Abstract
:1. Introduction
2. Methodology
2.1. Search Strategy
2.2. Inclusion Criteria
- Articles in English that discuss parallel robots for the rehabilitation of the neck, shoulder, wrist, hip, and ankle.
- Articles in English that discuss parallel robots for assistance related to the neck, shoulder, wrist, hip, and ankle.
- Articles in English that discuss parallel robots for humanoid applications focusing on the neck, shoulder, wrist, hip, and ankle.
- Parallel robots with three or more degrees of freedom.
- Articles discussing parallel robots at either the conceptual or prototype level of technological development.
2.3. Exclusion Criteria
- Articles that do not discuss parallel robots.
- Articles unrelated to rehabilitation involving parallel robots.
- Articles unrelated to assistance involving parallel robots.
- Articles unrelated to humanoid applications involving parallel robots.
2.4. Quality Assessment
2.5. Data Extraction
2.6. Search Performance
2.7. Systematic Review
3. Biomechanics of the Human Joints
- Anatomical planes:Sagittal plane (or median plane): Divides the body into left and right halves. Movement in this plane is forward and backward.Frontal plane (or coronal plane): Divides the body into anterior (front) and posterior (back) halves. Movement in this plane is side-to-side.Transverse plane (or axial/horizontal plane): Divides the body into superior (upper) and inferior (lower) halves. Movement in this plane involves rotation.
- Anatomical axes:Sagittal axis (or anteroposterior axis): Extends front to back and is perpendicular to the frontal plane. Movements around this axis include abduction and adduction.Frontal axis (or horizontal axis): Extends side to side and is perpendicular to the sagittal plane. Movements around this axis include flexion and extension.Vertical axis (or longitudinal axis): Extends top to bottom and is perpendicular to the transverse plane. Movements around this axis include internal and external rotation.
- Range of motion of human joints:The range of motion (ROM) varies depending on the specific joint and is influenced by factors such as age, gender, flexibility, and the individual’s physical condition. Table 1 presents the planes and axes of motion, types of motion, and ranges of motion for the neck, shoulder, hip, wrist, and ankle joints [34].
4. Parallel Robots and Applications in the Medical Field
- Rehabilitation robots are designed to assist individuals in regaining motor skills, functionality, and strength following injury or illness. Deployed in therapeutic settings, these devices aim to enhance the individual’s physical capabilities and long-term quality of life.
- Assistive robots are created to help individuals perform activities of daily living, such as dressing, running, or walking, when these activities are restricted due to disability or injury. These devices serve as aids to improve the individual’s quality of life, offering autonomy and independence.
- Humanoid robots represent an impressive advancement in technology, designed to mimic and replicate human form and behavior. These robots are built with anatomical features resembling those of humans, including heads, torsos, arms, and legs, enabling them to move and execute tasks in a manner similar to humans.Based on the preceding discussion, it is crucial to initially distinguish between parallel robots and their serial and hybrid counterparts. Following this differentiation, we can then delve into their applications in rehabilitation, assistance, and humanoid contexts, particularly focusing on specific joints like the neck, wrist, shoulder, hip, and ankle.
4.1. Distinctions between Serial, Parallel, and Hybrid Robots
4.2. Parallel Robot for Neck Joint
4.2.1. Parallel Robot for Neck Rehabilitation
4.2.2. Parallel Robot for Neck Assistance
4.2.3. Parallel Robot for Neck Humanoid
Author | Year | Country | Device | TRL | Mechanism | DoF | ToM | Actuator | Model | Tool |
---|---|---|---|---|---|---|---|---|---|---|
Gao et al. [39] | 2013 | China | NH | 1 | cable-driven | 3 | PR | NS | IK | M |
Gao et al. [40] | 2014 | China | NH | 2 | cable-driven | 3 | NS | NS | IK | M |
Gao et al. [41] | 2014 | China | NH | 1 | cable-driven | 3 | NS | NS | IK | M |
Jiang et al. [42] | 2015 | China | NH | 2 | cable-driven | 3 | NS | NS | IK | M |
Gao et al. [43] | 2017 | China | NH | 2 | cable-driven | 3 | PR | NS | IK | M |
Zhang et al. [36] | 2017 | USA | NA | 3 | 3-RRS | 3 | FE, RLB, RLR | NS | FK | M |
Zhang et al. [37] | 2018 | USA | NA | 3 | 3-RRR | 3 | FE, RLB, RLR | ER | IK | NS |
Liu et al. [38] | 2019 | China | NA | 3 | 3-RXS | 3 | FE, RLB, RLR | NS | IK | AN |
Lingampally et al. [1] | 2019 | India | NR | 3 | 3-RPS | 3 | RLR | EL | IK | M |
Zhang et al. [2] | 2019 | USA | NR | 3 | 3-RRR | 3 | FE, RLB, RLR | ER | D | M |
Quevedo et al. [3] | 2021 | Spain | NH | 3 | cable-driven | 3 | FE, RLR | ER | IK | M |
Lozano et al. [4] | 2022 | Mexico | NR | 4 | 4-SPS | 4 | NS | EL | D | M |
Zhang et al. [35] | 2023 | China | NR | 4 | cable-driven | 3 | FE, RLB, RLR | NS | IK | M |
4.3. Parallel Robot for Shoulder Joint
4.3.1. Parallel Robot for Shoulder Rehabilitation
4.3.2. Parallel Robot for Shoulder Assistance
4.3.3. Parallel Robot for Shoulder Humanoid
Author | Year | Country | Device | TRL | Mechanism | DoF | ToM | Actuator | Model | Tool |
---|---|---|---|---|---|---|---|---|---|---|
Chen et al. [53] | 2012 | China | SH | 2 | cable-driven | 7 | NS | ER | IK | AD |
Sekine et al. [50] | 2013 | Japan | SA | 2 | cable-driven | 3 | FE, AA, IER | PL | FK | ADLA |
Wang et al. [54] | 2013 | China | SH | 2 | 5-PMA | 5 | NS | P | FK | MS |
Klein et al. [44] | 2014 | UK | SR | 4 | 5R | 3 | NS | E | FK | CAD |
Sekine et al. [20] | 2015 | Japan | SA | 3 | 3-SPS/P | 3 | NS | PL | FIK | NS |
Enferadi et al. [45] | 2015 | Iran | SR | 2 | 3-RSS/S | 3 | RP | ER | IK | NS |
Enferadi et al. [46] | 2016 | Iran | SR | 2 | 3-RSS/S | 3 | NS | ER | IK | NS |
Hunt et al. [47] | 2016 | USA | SR | 3 | SPM | 3 | NS | EL | FIK | CAD |
Alfayad et al. [55] | 2016 | France | SH | 3 | 2-UPUR/RU | 2 | PRY | EL | IK | NS |
Jiang et al. [56] | 2017 | China | SH | 3 | cable-driven | 2 | NS | ER | NS | NS |
Leal-Naranjo et al. [51] | 2018 | Italy | SA | 3 | 3-RRR | 3 | FE | ER | IK | NS |
Leal-Naranjo et al. [19] | 2018 | Mexico | SA | 2 | 3-RRR | 3 | FE | ER | IK | AD |
Hunt et al. [52] | 2018 | USA | SA | 3 | 4B-SPM | 3 | NS | ER | FIK | M |
Lui et al. [57] | 2019 | China | SH | 3 | 5-PMA | 5 | NS | PL | FIK | M-AD |
Bai et al. [58] | 2019 | Denmark | SH | 3 | 3-RRR | 3 | RP | ER | FIK | NS |
Niyetkaliyev et al. [48] | 2020 | Australia | SR | 2 | cable-driven | 3 | AA | NS | IK | CAD |
Hunt et al. [49] | 2021 | USA | SR | 3 | 4B-SPM | 7 | FE, AA | EL | FIK | NS |
Wang et al. [59] | 2021 | China | SH | 2 | 5R | 3 | FE, AA, IER | ER | FK | AD |
Chen et al. [60] | 2023 | China | SH | 4 | cable-driven | 3 | FE, AA, L | ER | IK | NS |
4.4. Parallel Robot for Wrist Joint
4.4.1. Parallel Robot for Wrist Rehabilitation
4.4.2. Parallel Robot for Wrist Assistance
4.4.3. Parallel Robot for Wrist Humanoid
Author | Year | Country | Device | TRL | Mechanism | DoF | ToM | Actuator | Model | Tool |
---|---|---|---|---|---|---|---|---|---|---|
Serracin et al. [68] | 2012 | Spain | WA | 3 | 2-UPS/S | 2 | NS | EL | IK | M |
Chaparro et al. [73] | 2013 | Mexico | WH | 3 | 3-SPS/S | 3 | RPY | EL | FK | NS |
Pehlivan et al. [61] | 2013 | USA | WR | 3 | 3-RPS | 2 | FE, AA | PL | FIK | M |
Kong et al. [74] | 2015 | UK | WH | 2 | 3-4R | 2 | NS | NS | IK | NS |
Lu et al. [75] | 2017 | China | WH | 3 | 5-SPM | 5 | NS | EL | FIK | NS |
Bian et al. [62] | 2017 | China | WR | 3 | 2-URR/RRS | 3 | FE, AA | ER | IK | NS |
Lee et al. [69] | 2018 | South Korea | WA | 3 | 2-RRR | 3 | FE, AA | ER | FIK | NS |
Kitano et al. [6] | 2018 | Japan | WR | 3 | 3-RRR | 3 | FE, AA, SP | ER | FIK | NS |
Wu et al. [76] | 2018 | China | WH | 3 | 2-PUU/RPS | 2 | TR | ER, EL | IK | NS |
He et al. [77] | 2019 | China | WH | 2 | cable-driven | 4 | NS | ER | IK | NS |
Pang et al. [9] | 2020 | China | WH | 3 | cable-driven | 2 | FE, AA | ER | IK | NS |
Wang et al. [63] | 2021 | China | WR | 3 | 6-SPS/PS | 3 | FE, AA, SP | PL | FIK | NS |
Lee et al. [70] | 2021 | Korea | WA | 3 | 2-CSPM | 2 | FE, AA, SP | EL | FIK | NS |
Wang et al. [59] | 2021 | China | WH | 2 | 3-UPS/S | 2 | FE, SP | EL | FK | AD |
López et al. [71] | 2022 | UK | WA | 3 | 2-RRRPR/RRPR | 3 | NS | EL | IK | M |
Goyal et al. [64] | 2022 | Australia | WR | 3 | 3-RPR | 3 | FE, AA, PS | PMA | IK | NS |
Bazman et al. [78] | 2022 | Turkey | WH | 2 | 3-RSR/UUP | 2 | RPY | NS | FK | MS |
Sanjuan et al. [72] | 2022 | USA | WA | 2 | cable-driven | 2 | NS | NS | IK | NS |
Li et al. [79] | 2022 | China | WH | 2 | 3-RPS/US | 2 | NS | EL | IK | NS |
Li et al. [65] | 2023 | China | WR | 4 | cable-driven | 3 | FE, AA, SP | ER | IK | M |
Goyal et al. [66] | 2023 | Australia | WR | 4 | 4-BMA | 3 | FE, AA, SP | PL | IK | NS |
Goyal al. [67] | 2023 | Australia | WR | 4 | 4-BMA | 3 | FE, AA, SP | PL | IK | NS |
4.5. Parallel Robot for Hip Joint
4.5.1. Parallel Robot for Hip Rehabilitation
4.5.2. Parallel Robot for Hip Assistance
4.5.3. Parallel Robot for Hip Humanoid
Author | Year | Country | Device | TRL | Mechanism | DoF | ToM | Actuator | Model | Tool |
---|---|---|---|---|---|---|---|---|---|---|
Rastegarpanah et al. [80] | 2016 | UK | HR | 4 | 6-UPS | 6 | FE | EL | FK | M |
Jiang et al. [22] | 2017 | China | HH | 3 | PMA | NS | NS | PL | FIK | NS |
Wang et al. [86] | 2017 | China | HH | 2 | 4-SPS/CU | 2 | NS | EL | NS | NS |
Russo et al. [87] | 2018 | Italy | HH | 3 | 4-SPS | 4 | NS | EL | IK | NS |
Ren et al. [83] | 2019 | China | HA | 3 | 6-SPS | 6 | NS | PL | FIK | NS |
Zhang et al. [81] | 2020 | China | HR | 3 | 2-UPS/RRR | 3 | FE, AA, IER | EL | FK | NS |
Song et al. [84] | 2020 | China | HA | 2 | 4-RPS | 3 | NS | NS | FK | NS |
Shi et al. [82] | 2022 | China | HR | 3 | 2-UPS/RRR | 3 | FE-AA, IER | EL | FIK | NS |
Wang et al. [85] | 2023 | China | HA | 4 | 2-UPS+S | 2 | IER | EL | IK | NS |
4.6. Parallel Robot for Ankle Joint
Author | Year | Country | Device | TRL | Mechanism | DoF | ToM | Actuator | Model | Tool |
---|---|---|---|---|---|---|---|---|---|---|
Wang et al. [88] | 2012 | China | AR | 2 | 3-SPS/SP | 3 | PD, IE, AA | NS | FIK | M |
Saglia et al. [89] | 2013 | Italy | AR | 4 | 3-UPS/U | 2 | PD, IE | EL | FK | NS |
Wang et al. [90] | 2013 | China | AR | 2 | 3-RUS/RRR | 3 | PD, IE, AA | ER | IK | AD |
Jamwal et al. [91] | 2014 | India | AR | 4 | PMA | 3 | PD, IE, AA | PL | FK | M |
Jamwal et al. [92] | 2015 | India | AR | 2 | PMA | 3 | NS | PM | FIK | M |
Vallés et al. [93] | 2015 | Spain | AR | 3 | 3-PRS | 3 | PD, IE | EL | IK | ROS |
Jamwal et al. [94] | 2016 | Kazakhstan | AR | 4 | PMA | 3 | PD, IE, AA | PM | FK | NS |
Azar et al. [96] | 2016 | Iran | AR | 3 | 6-UPS | 6 | NS | PM | IK | NS |
Ruiz-Hidalgo et al. [95] | 2016 | Mexico | AR | 3 | 3-SPR | 3 | NS | EL | IK | AD |
Rosado et al. [97] | 2017 | Mexico | AR | 2 | 2-RRSP | 2 | PD, IE | ER | NS | M |
Rosado et al. [98] | 2017 | Mexico | AR | 3 | 2-RRSP | 2 | PD, IE | ER | NS | AD |
Du et al. [99] | 2017 | China | AR | 2 | 3-RRS | 3 | PD, IE | EL | IK | NS |
Zhang et al. [100] | 2017 | New Zealand | AR | 2 | 4-PMA | 3 | PD, IE, AA | PM | IK | NS |
Liao et al. [15] | 2018 | China | AR | 2 | 3-PSP | 3 | PD, IE | NS | IK | NS |
Rastegarpanah et al. [17] | 2018 | UK | AR | 3 | 6-UPS/3SPR | 9 | NS | NS | IK | NS |
Jamwal et al. [101] | 2018 | Kazakhstan | AR | 4 | PMA | 3 | PD, IE, AA | PM | IK | LV |
Wang et al. [102] | 2019 | China | AR | 3 | 2-SPS | 2 | PD, IE | EL | FK | NS |
Naruhmi et al. [103] | 2019 | Indonesia | AR | 3 | 3(rR)PS | 3 | NS | NS | FK | NS |
Zuo et al. [14] | 2020 | China | AR | 2 | 2-UPS/RRR | 3 | PD, IE, AA | EL | IK | NS |
Li et al. [104] | 2020 | China | AR | 3 | 2-UPS/RRR | 3 | PD, IE, AA | EL | IK | NS |
Russo et al. [105] | 2020 | UK | AR | 2 | cable-driven | 3 | PD, IE, AA | EL | NS | NS |
Li et al. [106] | 2020 | China | AR | 3 | 2-UPS/RRR | 3 | PD, IE, AA | EL | IK | M |
Pulloquinga et al. [107] | 2021 | Spain | AR | 3 | 3-UPS/RPU | 4 | NS | EL | IK | M, LV |
Liu et al. [108] | 2022 | China | AR | 2 | 2-UPU/RPU | 2 | PD, IE | PM | IK | NS |
Valencia-Segura et al. [109] | 2023 | Mexico | AR | 3 | 4-bar | 2 | PD, IE, AA | NS | IK | CAD |
Wu et al. [110] | 2023 | China | AR | 4 | 6-SSP, 3-RPS | 9 | PD, IE, AA | EL | IK | NS |
Shi et al. [111] | 2023 | China | AR | 4 | 3-RRR | 3 | PD, IE, AA | ER | IK | M |
Zuo et al. [112] | 2023 | China | AR | 4 | RPUR, SPR | 5 | PD, IE, AA | ER | IK | NS |
Zermane et al. [113] | 2023 | France | AR | 4 | 3-PRS | 3 | PD, IE, AA | ER | IK | SA |
Zhang et al. [114] | 2023 | China | AR | 4 | 2-UPU/PRPS | 3 | PD, IE, AA | EL | IK | M |
5. Discussion
5.1. Timeline of Parallel Robots from 2012 to 2023
- Rehabilitation focus: Rehabilitative robotics present a variety of versatile solutions, from ankle robots equipped with impedance control and redundant actuation, to teleoperable, modular ankle devices and multi-objective-optimized wearable ankle robots. Shoulder and wrist rehabilitation benefit from adaptive controllers, multi-DoF prosthetics, and anti-vibration control technologies.Ankle rehabilitation has been a consistent area of interest every year, with advances in control algorithms [89], wearable designs [91,92,93], hybrid mechanisms [15], natural motion mimicry [102], and high-torque applications [14,104,105,106]. As of 2023, rehabilitation techniques have expanded to treat balance disorders [110] and offer solutions for vertigo diagnosis [113].
- Cable-driven and parallel robots: Starting in 2012 with applications like shoulder movement simulation and ankle rehabilitation, there has been a clear focus on cable-driven and parallel mechanisms. These designs emphasize human mimicry, offering smooth and organic movements. Examples include neck movements [39,40,41], wrist motion [68,74], and shoulder movements [45,53]In terms of mimicking human biomechanics, cable-driven robots excel in recreating neck and cervical spine movements, while various exoskeletons and prosthetics, such as 7DoF shoulder and arm mechanisms, offer enhanced spatial characteristics.
- Humanoid design: The timeline indicates the progression in bionic and humanoid designs. From bionic joints in 2013 [54] to more comprehensive hybrid humanoid arms in 2021 [59,59], there has been an evident push towards creating robots that closely emulate human characteristics. The introduction of LARMbot 2 in 2018 [87] demonstrates the practical implementations of these humanoid designs.Humanoid robots feature innovations like bionic joints, pneumatic-muscle-driven manipulators, and multi-objective-optimized trajectory controls, designed for speed, stability, and energy efficiency.
- Neck and shoulder rehabilitation: Starting from 2013 with the cable-driven robot mimicking human neck movements [39], there has been a sustained focus on neck and shoulder rehabilitation mechanisms over the years. By 2021, there was a move towards more flexible and soft mechanisms for neck rehabilitation [3], further improving in 2023 with cable-driven exoskeletons for cervical rehabilitation [35].
5.2. Advancements in Parallel Robots from 2012 to 2023
- Parallel robots for rehabilitation:Firstly, it is evident that China has emerged as a significant contributor to research in this field, accounting for 37.3% of the total articles. This underscores China’s robust presence in parallel robot research, particularly in the area of rehabilitation for various joints.Mexico accounts for 9.8% of the total articles. This underscores the active participation of researchers from this country in investigating the applications of parallel robots, especially in the neck and ankle areas. On the other hand, each of the following countries: the United States, the United Kingdom (UK), and Australia, accounts for 7.8% of the total articles.Moreover, while individual countries like India, Iran, each contributed a smaller percentage, they collectively made up a significant portion of the total articles, at 5.9% each. This fact demonstrates a global interest and investment in advancing the field of parallel robot rehabilitation.Conversely, some countries, such as Spain and Kazakhstan, accounting for 3.9%, have demonstrated a more balanced distribution of articles across different joint areas, indicating a diverse research focus.It is important to note that there are countries, such as Japan, Italy, New Zealand, Indonesia and France, that each contributed to the total with a smaller percentage, starting from 2.0%. While their contributions may be comparatively modest, they nonetheless play a role in enriching the overall body of knowledge in the field of parallel robot applications for rehabilitation.
- Parallel robots for assistance:The United States (USA) leads in contributions to research in this field, accounting for 31.3% of the total articles. This statistic suggests that the USA is vigorously engaged in research on parallel robots for assistance, with particular emphasis on the neck, shoulder, and wrist areas. China follows closely, contributing 25.0% of the articles, with a focus on assistance for the neck and hip.Japan also has a significant presence, contributing 12.5% of the articles and concentrating primarily on shoulder assistance. This highlights Japan’s active involvement in research concerning parallel robots designed for assistance purposes.The analysis revealed that multiple countries, including Italy, Mexico, South Korea, and the United Kingdom (UK), each contributed 6.3% to the total body of articles. These articles were predominantly centered on shoulder and wrist assistance.The data indicate a widespread interest in parallel robots for assistance on a global scale. While the USA, China, and Japan emerged as the major contributors, other countries are also actively participating in research in this field, showing a dispersed research effort.The lack of contributions focusing on certain body parts, such as the ankle, in some countries may suggest that the research in those nations is primarily oriented toward other specific areas of assistance.
- Parallel robots for humanoids:China is the most prominent contributor to research in this field, responsible for 76.9% of the total articles published. This high percentage underscores a significant focus on parallel robots for humanoids within the Chinese research community. In terms of specific body parts, China’s contributions span articles related to the neck, shoulder, wrist, and hip.Several other countries, including France, Denmark, Mexico, the United Kingdom (UK), Turkey, and Italy, have also made contributions, albeit to a lesser extent. Each of these countries accounts for 3.8% of the total number of articles.
5.3. Technology Readiness Levels—TRLs
- Parallel robots for rehabilitation:The lack of articles at TRL 1 indicates that most research publications have moved beyond foundational scientific principles to more advanced stages. with 25.49% of the total articles, TRL 2 serves as a transitional phase from theoretical concepts to practical experimentation. The notable concentration at TRL 2 suggests that researchers are keenly exploring and prototyping new approaches to rehabilitation using parallel robots, especially for the shoulder and ankle regions.At 45.10%, TRL 3 boasts the largest percentage of articles, indicating that a significant volume of research has progressed to the prototype-building and proof-of-concept stages. The range of body parts covered (neck, shoulder, wrist, hip, and ankle) demonstrates a broad investigation into the applications of parallel robots in various rehabilitation contexts.Articles at TRL 4 make up 29.41% of the total publications. These studies imply that some research endeavors have reached the level of system integration and functional testing. The existence of articles at this TRL suggests the ongoing refinement of parallel robot systems, potentially bringing them closer to practical implementation in rehabilitation settings.
- Parallel robots for assistance:TRL 1 has no corresponding articles, suggesting that publications are primarily focused on concepts beyond initial scientific principles. Articles at TRL 2 account for 25.0% of the total, indicating a transition in research efforts toward practical experimentation and validation, particularly in the contexts of shoulder and wrist assistance.With 68.75% of the total articles classified under TRL 3, the research community has made significant strides in developing prototypes and demonstrating the feasibility of parallel robot systems for assistance across various body parts. The high concentration of articles at TRL 3 signifies a strong emphasis on constructing functional prototypes with the potential for real-world applications.Of the total articles, 6.25% are classified under TRL 4. This may indicate that research has advanced to the stages of system integration, advanced testing, or practical implementation.The distribution of TRLs across different body parts provides insights into the areas that have garnered more attention in terms of technological development for assistance. While neck, shoulder, and wrist assistance have seen notable progress, ankle assistance has not yet advanced beyond TRL 2.
- Parallel robots for humanoids:Articles at TRL 1 and TRL 2 together account for a collective 50.0% of the total. This suggests a substantial focus on both theoretical groundwork (TRL 1) and practical experimentation (TRL 2). Both neck and shoulder areas have received particular attention at these early stages.Articles classified under TRL 3 constitute the largest percentage, making up 46.15% of the total. This indicates that researchers have moved beyond initial theoretical concepts to the active development and validation of prototypes. The distribution across various body parts reflects a comprehensive focus on the application of parallel robots in humanoid systems.There are 3.85% corresponding articles at TRL 4, suggesting that research has advanced to the stage of system integration or operational testing.The distribution of TRLs across different body parts provides insights into the areas that have received the most attention in terms of technological development for humanoid applications. Notable progress has been observed across TRLs for the shoulder and wrist.
5.4. Design, Number of Degrees of Freedom, and Kinematics Structure in Parallel Robotics
5.4.1. Design Principles
5.4.2. Number of Degrees of Freedom and Kinematic Structure
- Neck joint:For the neck joint, the dominant kinematic structures are primarily based on a 3DoF framework. In the rehabilitation sphere, there are models such as 3-RPS [1] and 3-RRR [2]. In the context of assistance robots, configurations like 3-RRS [36], 3-RRR [37], and 3-RXS [38] are used. Humanoid robotics often favor cable-driven mechanisms [3,39,41,42,43]. A 4DoF structure, represented by the 4-SPS model [4], is also common in the rehabilitation sector.
- Shoulder joint:Given its complex nature, the shoulder joint exhibits a diverse range of kinematic structures. In humanoid robots, 2DoF mechanisms like 2-UPUR/RU [55] and cable-driven [56] systems are prominent. As the DoF expand to 3 and 5, the rehabilitation domain presents an array of models, including 5R [44], 3-RSS/S [45], and SPM [47]. In the assistance robotics realm, structures such as 3-SPS/P [20], 3-RSS/S [46], and 3-RRR [19,51] emerge. The 7DoF mechanisms, including designs like 4B-SPM [49] and cable-driven [50] methods, underscore the sophistication of this joint’s modeling.
- Wrist joint:Given its essential function in facilitating dexterity, the wrist showcases a broad spectrum of kinematic structures. In rehabilitation for a 2DoF wrist, the 3-RPS [61] configuration stands out. In humanoid applications, models evolve in complexity from 2-PUU/RPS [76] for 2DoF to designs like 5-SPM [75] for 5DoF. The ubiquitous presence of cable-driven [72] solutions across varying DoF emphasizes their role in ensuring flexibility and adaptability.
- Hip joint:For the 2DoF hip joint, while the rehabilitation and assistance domains remain relatively unexplored, humanoid designs have proposed models like 4-SPS/CU [86]. A 3DoF hip favors models like 2-UPS/RRR [81,82] in rehabilitation and 4-RPS [84] in assistance robotics. Interestingly, the 6DoF hip primarily features the 6-UPS [80,83] configuration, evident in both the rehabilitation and assistance domains.
- Ankle joint:The ankle, crucial for locomotion, has garnered significant attention in the rehabilitation sector. The multitude of designs for a 3DoF ankle, ranging from 3-SPS/SP [88] to 3-PSP [15], attests to this. The frequent inclusion of configurations like PMA in multiple references underscores its significance. Higher-DoF designs, such as the 6-UPS [96] for 6DoF and 6-UPS/3SPR [17] for 9DoF, suggest an emphasis on advancing ankle dexterity in robotics.The choice of kinematic structure affects other design parameters like the system’s strength, flexibility, control complexity, and efficiency. It becomes evident that the technological advances in rehabilitation, assistance, and humanoid robotics are significantly intertwined with the complexities of human anatomy. The extensive research cited above underscores the relentless endeavors of scientists and engineers to emulate human-like movement and function. As robotics continues its foray into human-centric applications, such insights will become pivotal. They not only reflect the current state of art but also hint at the vast potential awaiting in the future of biomechanics and robotics.
5.5. Assessment of Workspace, Functional Capabilities, and Performance Methods in Parallel Robotics
- Workspace:Workspace analysis and optimization are recurring themes in a range of robotic technologies, often serving medical and rehabilitation purposes. Various studies have emphasized different methods and objectives to optimize workspace. For instance, Gao et al. [39,41] and Enferadi et al. [45] used simulations and genetic algorithms, respectively, to assess workspace under positive cable tension constraints and maximize it, with Enferadi’s work noting the advantage of a singularity-free workspace. Niyetkaliyev’s hybrid mechanism [48] covered a full range of shoulder movements in a singularity-free workspace, while Sekine et al. [20] and Song et al. [84] focused on prosthetic arms and hips that offered increased and rotating workspaces, respectively. Zhang et al. [100] employed geometric parameter optimization to prevent workspace singularities in an ankle rehabilitation robot. The studies of Lee et al. [69] and Serracin et al. [68] considered enhancing workspace efficiency and user comfort, and Wu and Chaparro-Altamirano [73] addressed orientation workspace and workspace calculations. Additional research by Zhang et al. [81], Liao et al. [15], Rastegarpanah et al. [17], Naruhmi et al. [103], and Zuo et al. [14] delved into adjustable workspaces, the expansion of central points on moving platforms, and broad workspaces for ankle rehabilitation, often validated through simulations, prototypes, or theoretical analyses.Overall, the workspace is considered a critical design factor, evaluated and optimized through various methods to meet different performance requirements.
- Functional capabilities:The functional capabilities of parallel robots, such as dexterity, manipulability, and range of motion, are critical for their application in rehabilitation and assistive technologies.
- Performance evaluation methods:The performance evaluation of parallel robots is multi-faceted, typically incorporating metrics such as speed [28,59], accuracy [33,53,57,84,104,108], repeatability, load-carrying capacity [79,80], energy efficiency, and safety [96]. Methods for performance evaluation include computational methods, and simulations for statistical analysis and finite element analysis (FEA) for mechanical property evaluation are popular choices [38].Furthermore, various software tools were prevalent for simulation and analysis in the studies reviewed. MATLAB, SimScape Multibody [54,78], ADAMS [19,53,59,90,95,98,98], and ANSYS [38] each offer unique capabilities for evaluating different aspects of robot performance, workspace, and function. Their choice often depends on the specific requirements of the study.Based on existing research, MATLAB is commonly used to simulate parallel robots because of its matrix-handling abilities, algorithm implementation, function representation, user interface creation, and interoperability. SimScape Multibody, part of MATLAB’s Simulink suite, offers block-diagram-based modeling for rigid-body mechanics, describing kinematics and dynamics through blocks representing bodies and joints. This enables quick validation and offers 3D visualization for system movement comprehension. MSC ADAMS facilitates the study of dynamics, load distribution, and forces in mechanical systems by allowing the creation of virtual prototypes underpinned by real-world physics. Meanwhile, ANSYS specializes in kinematic simulations, providing detailed analyses of motion and structural parameters, including rotation angles and force requirements.
5.6. Material Selection in the Development of Parallel Robotics
- MetalsAluminum: This metal is highly prized for its advantageous strength-to-weight ratio, thermal and electrical conductivity, and intrinsic resistance to corrosion. It is often the material of choice for constructing lightweight robotic frameworks. This material was used in a hybrid parallel robot designed for foot rehabilitation [17] and a hybrid exoskeleton for elbow–forearm–wrist rehabilitation [62].Stainless steel: Renowned for its exceptional durability and corrosion resistance, stainless steel finds utility in applications that demand high mechanical strength and rigidity. This material was utilized in a distal arm exoskeleton for stroke and spinal cord injury rehabilitation [7] and a rope-driven mechanism for wrist rehabilitation [9].Carbon steel: Medium-carbon steels like 1045 are used in applications where a balance of strength and ductility is required. This material was utilized in a novel bio-inspired and cable-driven hybrid parallel shoulder mechanism [48].
- PlasticsThese polymers are commonly selected for components that necessitate low mechanical strength but prioritize lightweight characteristics. ABS (acrylonitrile butadiene tyrene) is a type of thermoplastic polymer. It is a copolymer made from three different monomers: acrylonitrile, butadiene, and styrene. Acrylonitrile provides chemical resistance and thermal stability. Butadiene contributes toughness and impact resistance. Styrene offers rigidity and a glossy finish. This material was employed in a parallel robot designed for a prosthetic arm aimed at shoulder disarticulation [19], a rigid–flexible parallel mechanism for a neck brace [38], a prosthetic arm [51], and a humanoid robot with parallel architectures [87].
- Composite materialsCarbon-fiber composites: Valued for their extraordinary strength-to-weight ratios and rigidity, these composites are ideal for crafting structural components that must be both resilient and lightweight. This material was utilized in a hybrid prosthetic mechanism for transfemoral amputees [18].
- Advanced or ’smart’ materialsMagnetorheological fluids: These fluids are integrated into adaptive control systems to modulate mechanical properties in real time. Although this material has not yet been used in parallel robots, it is important to note that it can be utilized human prosthesis [116].Shape-memory alloys (SMAs): Predominantly used in the design of actuators and responsive joints, these alloys enable a broad range of functional capabilities. Although this material has not yet been used in parallel robots, it is important to note that it can be utilized in robotic and biomedical applications [117].Piezoelectric materials: These are incorporated in systems requiring ultra-precise micromovements and sensing applications. Although this material has not yet been used in parallel robots, it is important to note that it can be utilized in robotic and biomedical applications [118].
- Soft materialsSilicone: Predominantly employed in soft robotics, silicone’s deformable yet resilient nature confers flexibility to the robot design. This material was used in a soft robotic neck that employed a parallel robot [3].Elastomers: Capable of undergoing shape or stiffness alterations in response to electrical or thermal stimuli, elastomers are gaining traction in soft robotic applications. This material was utilized in a parallel lower limb based on pneumatic artificial muscles [22] and a soft parallel robot based on pneumatic artificial muscles for wrist rehabilitation [63].
5.7. Critical Technological Challenges and Future Prospects in Rehabilitation, Assistance, and Humanoids
- Key technological challengesPrecision and reliability: Both rehabilitation and assistive robotics demand highly precise and reliable systems. The challenge extends to humanoid robots, which must interact safely and effectively in human-centric environments. The need for high precision and fail-safe operation in medical rehabilitation sets a challenging bar for system performance. Addressing issues related to sensor accuracy and the reliability of actuators is of paramount importance.User interface and experience: As these systems are ultimately designed for human use, developing intuitive, user-friendly interfaces that can cater to a diverse demographic is a significant hurdle. The end-users range from medical professionals to patients and the general public. Designing interfaces that are universally intuitive is an ongoing challenge.Material constraints: Material choices should balance durability, cost, and biocompatibility, especially for wearable devices. Ensuring that all materials and operational modalities are biocompatible, sterile, and safe for long-term use requires rigorous testing and often leads to increased costs.Scalability and affordability: Creating systems that are economically viable to manufacture at scale while maintaining high-quality performance presents an ongoing challenge.
- Impediments to commercializationRegulatory hurdles: Approvals for medical and assistive devices are lengthy and require substantial investment in clinical trials and validation studies.Cost factor: Advanced materials and smart systems drive up the manufacturing costs, making it difficult to position these products as affordable solutions.
- Future directionsTo realize the full potential of parallel robotic systems in the rehabilitation sector, future work needs to focus on solving the technological issues mentioned above. Solutions may lie in material innovations and machine learning algorithms for adaptive control. This would facilitate commercial transitions but also pave the way for more effective and accessible rehabilitation and assistance technologies.
6. Conclusions
- The data presented in Table 8 highlight the global interest and collaborative efforts in researching parallel robots for rehabilitation across various joint areas. China, the USA, and several other countries have actively contributed to this burgeoning field, each with a specific focus on particular joints. This comprehensive effort underscores the significance of parallel robot technology in furthering our understanding of human movement and enabling assistance across various joints.
- As the field of robotics continues to evolve, international collaboration can collectively drive advancements and shape the future of robotic technologies in rehabilitation, assistance, and humanoid applications.
- Technological development is a multifaceted process influenced by numerous factors. In the case of parallel robots, several challenges may have impeded further advancement. These could include technical limitations requiring complex and advanced solutions, as well as the inherent complexity of integrating sophisticated mechanical and electronic systems and control algorithms. Meeting these challenges necessitates ongoing research and development efforts.
- Parallel mechanisms offer multiple advantages over their serial counterparts, including greater rigidity, load capacity, precision, and speed. These characteristics make them well-suited for applications requiring high precision, such as rehabilitation and assistance in the neck, shoulder, wrist, hip, and ankle joints. Due to their design and configuration, parallel robots can distribute loads across their kinematic chains, enabling the manipulation of heavier objects and tasks requiring greater force.
- Parallel robots hold significant potential for rehabilitation, assistance, and humanoid applications, but many challenges and opportunities remain. These include the need for advanced sensors and control systems to improve accuracy and minimize movement errors.
- Looking to the future, continuous technological advancement and collaboration among the scientific community, industry, and healthcare professionals could make parallel robots a mainstay in the market. Their applications could extend to a wide range of sectors, including but not limited to the automotive, aerospace, and construction industries, as well as military training, medicine, and surgery.
Author Contributions
Funding
Conflicts of Interest
References
- Lingampally, P.; Selvakumar, A. A kinematic and workspace analysis of a parallel rehabilitation device for head-neck injured patients. FME Trans. 2019, 47, 405–411. [Google Scholar] [CrossRef]
- Zhang, H.; Chang, B.-C.; Andrews, J.; Mitsumoto, H.; Agrawal, S. A robotic neck brace to characterize head-neck motion and muscle electromyography in subjects with amyotrophic lateral sclerosis. Ann. Clin. Transl. Neurol. 2019, 6, 1671–1680. [Google Scholar] [CrossRef] [PubMed]
- Quevedo, F.; Muñoz, J.; Castano Pena, J.A.; Monje, C.A. 3D model identification of a soft robotic neck. Mathematics 2021, 9, 1652. [Google Scholar] [CrossRef]
- Lozano, A.; Ballesteros, M.; Cruz-Ortiz, D.; Chairez, I. Active neck orthosis for musculoskeletal cervical disorders rehabilitation using a parallel mini-robotic device. Control Eng. Pract. 2022, 128, 105312. [Google Scholar] [CrossRef]
- Keller, U.; Klamroth, V.; van Hedel, H.J.A.; Riener, R. ChARMin: A robot for pediatric arm rehabilitation. In Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 6–10 May 2013; pp. 3908–3913. [Google Scholar]
- Kitano, Y.; Tanzawa, T.; Yokota, K. Development of wearable rehabilitation device using parallel link mechanism: Rehabilitation of com pound motion combining palmar/dorsi flexion and radial/ulnar deviation. Robomech J. 2018, 5, 13. [Google Scholar] [CrossRef]
- Pehlivan, A.U.; Celik, O.; O’Malley, M.K. Mechanical design of a distal arm exoskeleton for stroke and spinal cord injury rehabilitation. In Proceedings of the IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland, 29 June–1 July 2011; pp. 1–5. [Google Scholar]
- Pehlivan, A.U.; Sergi, F.; O’Malley, M.K. A subject-adaptive controller for wrist robotic rehabilitation. IEEE/ASME Trans. Mechatron. 2015, 20, 1338–1350. [Google Scholar] [CrossRef]
- Pang, Z.; Wang, T.; Yu, J.; Liu, S.; Zhang, X.; Jiang, D. Design and analysis of a flexible, elastic, and rope-driven parallel mechanism for wrist rehabilitation. Appl. Bionics Biomech. 2020, 2020, 8841400. [Google Scholar] [CrossRef]
- Liu, Q.; Zuo, J.; Zhu, C.H.; Quan, S. Design and control of soft rehabilitation robots actuated by pneumatic muscles: State of the art. Future Gener. Comput. Syst. 2020, 113, 620–634. [Google Scholar] [CrossRef]
- Dong, M.; Zhou, Y.; Li, J.; Rong, X.; Fan, W.; Zhou, X.; Kong, Y. State of the art in parallel ankle rehabilitation robot: A systematic review. J. Neuroeng. Rehabil. 2021, 18, 52. [Google Scholar] [CrossRef]
- Hussain, S.; Jamwal, P.K.; Ghayesh, M.H. State-of-the-art robotic devices for ankle rehabilitation: Mechanism and control review. Proc. Inst. Mech. Eng. Part H J. Eng. Med. 2017, 231, 1224–1234. [Google Scholar] [CrossRef]
- Jamwal, P.K.; Hussain, S.; Xie, S.Q. Review on design and control aspects of ankle rehabilitation robots. Disabil. Rehabil. Assist. Technol. 2015, 10, 93–101. [Google Scholar] [CrossRef] [PubMed]
- Zuo, S.; Li, J.; Dong, M.; Zhou, X.; Fan, W.; Kong, Y. Design and performance evaluation of a novel wearable parallel mechanism for ankle rehabilitation. Front. Neurorobot. 2020, 14, 9. [Google Scholar] [CrossRef] [PubMed]
- Liao, Z.; Yao, L.; Lu, Z.; Zhang, J. Screw theory based mathematical modeling and kinematic analysis of a novel ankle rehabilitation robot with a constrained 3-PSP mechanism topology. Int. J. Intell. Robot. Appl. 2018, 2, 351–360. [Google Scholar] [CrossRef] [PubMed]
- Hussain, S.; Jamwal, P.K.; Vliet, P.V.; Brown, N.A.T. Robot assisted ankle neuro-rehabilitation: State of the art and future challenges. Expert Rev. Neurother. 2021, 21, 111–121. [Google Scholar] [CrossRef]
- Rastegarpanah, A.; Rakhodaei, H.; Saadat, M.; Rastegarpanah, M.; Marturi, N.; Borboni, A.; Loureiro, R.C.V. Path-planning of a hybrid parallel robot using stiffness and workspace for foot rehabilitation. Adv. Mech. Eng. 2018, 10, 1687814017754159. [Google Scholar] [CrossRef]
- Song, M.; Guo, S.; Oliveira, A.; Wang, X.; Qu, H. Design method and verification of a hybrid prosthetic mechanism with energy-damper clutchable device for transfemoral amputees. Front. Mech. Eng. 2021, 16, 747–764. [Google Scholar] [CrossRef]
- Leal-Naranjo, J.-A.; Torres-San Miguel, C.-R.; Ceccarelli, M.; Rostro-Gonzalez, H. Mechanical design and assessment of a low-cost 7-DOF prosthetic arm for shoulder disarticulation. Appl. Bionics Biomech. 2018, 2018, 4357602. [Google Scholar] [CrossRef] [PubMed]
- Sekine, M.; Xie, L.; Kawamura, K.; Yu, W. Improvement and quantification of spatial accessibility and disturbance responsiveness of shoulder prosthesis. Int. J. Adv. Robot. Syst. 2015, 12, 1–12. [Google Scholar] [CrossRef]
- Bajaj, N.M.; Spiers, A.J.; Dollar, A.M. State of the art in artificial wrists: A review of prosthetic and robotic wrist design. IEEE Trans. Robot. 2019, 35, 261–277. [Google Scholar] [CrossRef]
- Jiang, F.; Tao, G.; Li, Q. Analysis and control of a parallel lower limb based on pneumatic artificial muscles. Adv. Mech. Eng. 2017, 9, 1687814016685002. [Google Scholar] [CrossRef]
- Liu, G.; Lou, Y.; Li, Z. Singularities of parallel manipulators: A geometric treatment. IEEE Trans. Rob. Autom. 2003, 19, 579–594. [Google Scholar]
- Duan, X.; Yang, Y.; Cheng, B. Modeling and analysis of a 2-DOF spherical parallel manipulator. Sensors 2016, 16, 1485. [Google Scholar] [CrossRef] [PubMed]
- Silva, L.A.; Sebastian, J.M.; Saltaren, R.; Aracil, R.; Sanpedro, J. RoboTenis: Optimal design of a parallel robot with high performance. In Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, AB, Canada, 2–6 August 2005; pp. 2134–2139. [Google Scholar]
- Righettini, P.; Strada, R.; Cortinovis, F. Modal Kinematic Analysis of a Parallel Kinematic Robot with Low-Stiffness Transmissions. Robotics 2021, 10, 132. [Google Scholar] [CrossRef]
- Righettini, P.; Strada, R.; Zappa, B.; Lorenzi, V. Experimental set-up for the investigation of transmissions effects on the dynamic performances of a linear PKM. Mech. Mach. Sci. 2019, 73, 2511–2520. [Google Scholar]
- Wittenburg, J.; Likins, P. Dynamics of systems of rigid bodies. J. Appl. Mech. 1978, 45, 458. [Google Scholar] [CrossRef]
- Zubizarreta, A.; Marcos, M.; Cabanes, I.; Pinto, C.; Portillo, E. Redundant sensor based control of the 3RRR parallel robot. Mech. Mach. Theory 2012, 54, 1–17. [Google Scholar] [CrossRef]
- Hayes, M.J.D.; Zsombor-Murray, P.J.; Chen, C. Unified kinematic analysis of general planar parallel manipulators. J. Mech. Des. 2004, 126, 866–874. [Google Scholar] [CrossRef]
- Stoeffler, C.; Kumar, S.; Peters, H.; Bruls, O.; Muller, A.; Kirchner, F. Conceptual design of a variable stiffness mechanism in a humanoid ankle using parallel redundant actuation. In Proceedings of the 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), Beijing, China, 6–9 November 2018; pp. 462–468. [Google Scholar]
- Aracil, R.; Saltarén, R.J.; Sabater, J.M.; Reinoso, Ó. Robots Paralelos: Máquinas con un Pasado para una Robótica del Futuro. Rev. Iberoam. Autom. Inform. Ind. RIAI 2006, 3, 16–28. [Google Scholar]
- Alvarez-Perez, M.G.; Garcia-Murillo, M.A.; Cervantes-Sánchez, J.J. Robot-assisted ankle rehabilitation: A review. Disabil. Rehabil. Assist. Technol. 2020, 15, 394–408. [Google Scholar] [CrossRef] [PubMed]
- Taboadela, C.H. Goniometría: Una Herramienta para la Evaluación de las Incapacidades Laborales, 1st ed.; Asociart ART: Buenos Aires, Argentina, 2007; pp. 65–115. ISBN 978-987-9274-04-0. [Google Scholar]
- Zhang, H.; Ma, H.; Ren, J.; Shi, D.; Zhang, W. Design and Kinematic Analysis of a Cable-driven Exoskeleton for Cervical Rehabilitation. In Proceedings of the 2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA), Ningbo, China, 18–22 August 2023; pp. 1495–1500. [Google Scholar]
- Zhang, H.; Agrawal, S.K. Kinematic design of a dynamic brace for measurement of head/neck motion. IEEE Robot. Autom. Lett. 2017, 2, 1428–1435. [Google Scholar] [CrossRef]
- Zhang, H.; Agrawal, S.K. An active neck brace controlled by a joystick to assist head motion. IEEE Robot. Autom. Lett. 2018, 3, 37–43. [Google Scholar] [CrossRef]
- Liu, J.; Cheng, Y.; Zhang, S.; Lu, Z.; Gao, G. Design and analysis of a rigid-flexible parallel mechanism for a neck brace. Math. Probl. Eng. 2019, 2019, 9014653. [Google Scholar] [CrossRef]
- Gao, B.; Song, H.; Sun, L.; Tang, Y. Inverse kinematics and workspace analysis of a bio-inspired flexible parallel robot. In Proceedings of the 2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, Nanjing, China, 26–29 May 2013; pp. 138–143. [Google Scholar]
- Gao, B.; Hu, J.; Guo, S.; Li, W.; Kan, Q. Lateral bending models of spring spine for cable-driven parallel mechanism. In Proceedings of the 11th World Congress on Intelligent Control and Automation, Shenyang, China, 29 June–4 July 2014; pp. 3176–3180. [Google Scholar]
- Gao, B.; Song, H.; Zhao, J.; Guo, S.; Sun, L.; Tang, Y. Inverse kinematics and workspace analysis of a cable-driven parallel robot with a spring spine. Mech. Mach. Theory 2019, 76, 56–69. [Google Scholar] [CrossRef]
- Jiang, L.; Gao, B.; Zhao, J. Kinematic and static analysis of a cable-driven parallel robot with a flexible link spine. In Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China, 6–9 December 2015; pp. 31–36. [Google Scholar]
- Gao, B.; Zhu, Z.; Zhao, J.; Jiang, L. Inverse kinematics and workspace analysis of a 3 DOF flexible parallel humanoid neck robot. J. Intell. Robot. Syst. 2017, 87, 211–229. [Google Scholar] [CrossRef]
- Klein, J.; Roach, N.; Burdet, E. 3DOM: A 3 Degree of Freedom Manipulandum to Investigate Redundant Motor Control. IEEE Trans. Haptics 2014, 7, 229–239. [Google Scholar] [CrossRef] [PubMed]
- Enferadi, J.; Haghi, O.R. On the kinematics analysis of a novel spherical robot with unlimited rotation around an axis. In Proceedings of the 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM), Tehran, Iran, 7–9 October 2015; pp. 158–163. [Google Scholar]
- Enferadi, J.; Shahi, A. On the position analysis of a new spherical parallel robot with orientation applications. Robot. Comput. Integr. Manuf. 2016, 37, 151–161. [Google Scholar] [CrossRef]
- Hunt, J.; Lee, H.; Artemiadis, P. A Novel Shoulder Exoskeleton Robot Using Parallel Actuation and a Passive Slip Interface. J. Mech. Robot. 2016, 9, 011002. [Google Scholar] [CrossRef]
- Niyetkaliyev, A.S.; Sariyildiz, E.; Alici, G. Kinematic Modeling and Analysis of a Novel Bio-Inspired and Cable-Driven Hybrid Shoulder Mechanism. J. Mech. Robot. 2020, 13, 011008. [Google Scholar] [CrossRef]
- Hunt, J.; Lee, H. Optimizing the rigid or compliant behavior of a novel parallel-actuated architecture for exoskeleton robot applications. Front. Robot. AI 2021, 8, 596958. [Google Scholar] [CrossRef]
- Sekine, M.; Sugimori, K.; Gonzalez, J.; Yu, W. Optimization-based design of a small pneumatic-actuator-driven parallel mechanism for a shoulder prosthetic arm with statics and spatial accessibility evaluation. Int. J. Adv. Robot. Syst. 2013, 10, 286. [Google Scholar] [CrossRef]
- Leal-Naranjo, J.-A.; Ceccarelli, M.; Torres-San-Miguel, C.-R.; Aguilar-Perez, L.-A.; Urriolagoitia-Sosa, G.; Urriolagoitia-Calderón, G. Multiobjective optimization of a parallel manipulator for the design of a prosthetic arm using genetic algorithms. Lat. Am. J. Solids Struct. 2018, 15. [Google Scholar] [CrossRef]
- Hunt, J.; Lee, H. A New Parallel Actuated Architecture for Exoskeleton Applications Involving Multiple Degree-of-Freedom Biological Joints. J. Mech. Robot. 2018, 10, 051017. [Google Scholar] [CrossRef]
- Chen, W.; Chen, Q.; Liu, R.; Zhang, J. Homing algorithm analysis for a cable-driven 3-DOF shoulder joint. In Proceedings of the IEEE 10th International Conference on Industrial Informatics, Beijing, China, 25–27 July 2012; pp. 1170–1175. [Google Scholar]
- Wang, B.; Jin, Y.; Yan, T.; Cheng, M. Mechanism simulation and optimal design of five-link bionic joint driven by two antagonistic pneumatic muscles. Adv. Mech. Eng. 2013, 2013, 824085. [Google Scholar] [CrossRef]
- Alfayad, S.; Tayba, A.M.; Ouezdou, F.B.; Namoun, F. Kinematic Synthesis and Modeling of a Three Degrees-of-Freedom Hybrid Mechanism for Shoulder and Hip Modules of Humanoid Robots. J. Mech. Robot. 2016, 8, 041017. [Google Scholar] [CrossRef]
- Jiang, L.; Gao, B.; Zhu, Z. Design and Nonlinear Control of a 2-DOF Flexible Parallel Humanoid Arm Joint Robot. Shock Vib. 2017, 2017, 2762169. [Google Scholar] [CrossRef]
- Liu, K.; Chen, Y.; Xu, J.; Wu, Y.; Lu, Y.; Zhao, D. Fuzzy torque control of the bionic flexible manipulator actuated by pneumatic muscle actuators. Chin. J. Mech. Eng. 2019, 32, 79. [Google Scholar] [CrossRef]
- Bai, S.; Li, X.; Angeles, J. A review of spherical motion generation using either spherical parallel manipulators or spherical motors. Mech. Mach. Theory 2019, 140, 377–388. [Google Scholar] [CrossRef]
- Wang, Z.; Li, Y.; Sun, P.; Luo, Y.; Chen, B.; Zhu, W. A multiobjective approach for the trajectory planning of a 7-DOF serial-parallel hybrid humanoid arm. Mech. Mach. Theory 2021, 165, 104423. [Google Scholar] [CrossRef]
- Chen, W.; Feng, J.; Guan, Y.; Chen, W.; Wang, M. Improved Design and Modeling of a Series-Parallel Hybrid Modular Joint for Humanoid Arms. In Proceedings of the 2023 IEEE International Conference on Mechatronics and Automation (ICMA), Harbin, Heilongjiang, China, 6–9 August 2023; pp. 2389–2394. [Google Scholar]
- Pehlivan, A.U.; Sergi, F.; O’Malley, M.K. Adaptive control of a serial-in-parallel robotic rehabilitation device. In Proceedings of the 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), Seattle, WA, USA, 24–26 June 2013; pp. 1–6. [Google Scholar]
- Bian, H.; Chen, Z.; Wang, H.; Zhao, T. Mechanical design of EFW Exo II: A hybrid exoskeleton for elbow-forearm-wrist rehabilitation. In Proceedings of the 2017 International Conference on Rehabilitation Robotics (ICORR), London, UK, 17–20 July 2017; pp. 689–694. [Google Scholar]
- Wang, Y.; Xu, Q. Design and testing of a soft parallel robot based on pneumatic artificial muscles for wrist rehabilitation. Sci. Rep. 2021, 11, 1273. [Google Scholar] [CrossRef] [PubMed]
- Goyal, T.; Hussain, S.; Martinez-Marroquin, E.; Brown, N.A.T.; Jamwal, P.K. Impedance Control of a Wrist Rehabilitation Robot Based on Autodidact Stiffness Learning. IEEE Trans. Med. Robot. Bionics 2022, 4, 796–806. [Google Scholar] [CrossRef]
- Li, S.; Wang, Z.; Pang, Z.; Gao, M.; Duan, Z. Design and Analysis of a Hemispherical Parallel Mechanism for Forearm–Wrist Rehabilitation. Appl. Bionics Biomech. 2023, 2023, 5722499. [Google Scholar] [CrossRef]
- Goyal, T.; Hussain, S.; Martinez-Marroquin, E.; Brown, N.A.T.; Jamwal, P.K. Stiffness-Observer-Based Adaptive Control of an Intrinsically Compliant Parallel Wrist Rehabilitation Robot. IEEE Trans. Hum.-Mach. Syst. 2023, 53, 65–74. [Google Scholar] [CrossRef]
- Goyal, T.; Hussain, S.; Martinez-Marroquin, E.; Brown, N.A.T.; Jamwal, P.K. Learning Koopman Embedding Subspaces for System Identification and Optimal Control of a Wrist Rehabilitation Robot. IEEE Trans. Ind. Electron. 2023, 70, 7092–7101. [Google Scholar] [CrossRef]
- Serracín, J.R.; Puglisi, L.J.; Saltaren, R.; Ejarque, G.; Sabater-Navarro, J.M.; Aracil, R. Kinematic analysis of a novel 2-d.o.f. orientation device. Rob. Auton. Syst. 2012, 60, 852–861. [Google Scholar] [CrossRef]
- Lee, J.; Song, B.-W.; Yang, W. Design of exoskeleton-type wrist human–machine interface based on over-actuated coaxial spherical parallel mechanism. Adv. Mech. Eng. 2018, 10, 1687814017753896. [Google Scholar] [CrossRef]
- Lee, J.; Kim, H.; Yang, W. Development of wrist interface based on fully actuated coaxial spherical parallel mechanism for force interaction. Sensors 2021, 21, 8073. [Google Scholar] [CrossRef] [PubMed]
- López-Custodio, P.C.; Fu, R.; Dai, J.S.; Jin, Y. Compliance model of Exechon manipulators with an offset wrist. Mech. Mach. Theory 2022, 167, 1–18. [Google Scholar] [CrossRef]
- Sanjuan, J.D.; Sunny, M.S.H.; Ghommam, J.; Brahmi, B.; Wang, I.; Rahman, M.H. Optimal design of a cable-driven wrist prosthetic device. In Proceedings of the 9th International Conference of Control Systems, and Robotics (CDSR’22), Niagara Falls, ON, Canada, 2–4 June 2022; p. 108. [Google Scholar]
- Chaparro-Altamirano, D.; Zavala-Yoe, R.; Ramirez-Mendoza, R. Kinematic and workspace analysis of a parallel robot used in security applications. In Proceedings of the 2013 International Conference on Mechatronics, Electronics and Automotive Engineering, Morelos, Mexico, 19–22 November 2013; pp. 3–8. [Google Scholar]
- Kong, X.; Yu, J. Type Synthesis of Two-Degrees-of-Freedom 3-4R Parallel Mechanisms with Both Spherical Translation Mode and Sphere-on-Sphere Rolling Mode. J. Mech. Robot. 2015, 7, 041018. [Google Scholar] [CrossRef]
- Lu, Y.; Zhang, C.; Cao, C.; Liu, Y. Analysis of coordinated grasping kinematics and optimization of grasping force of a parallel hybrid hand. Int. J. Adv. Robot. Syst. 2017, 14, 1729881417716816. [Google Scholar] [CrossRef]
- Wu, G.; Niu, B. Dynamic stability of a tripod parallel robotic wrist featuring continuous end-effector rotation used for drill point grinder. Mech. Mach. Theory 2018, 129, 36–50. [Google Scholar] [CrossRef]
- He, J.; Xu, W.; Gao, B. Self-insulating joint design for live-line operation based on the cable-driven parallel-series mechanism. Appl. Sci. 2019, 10, 22. [Google Scholar] [CrossRef]
- Bazman, M.; Yilmaz, N.; Tumerdem, U. An Articulated Robotic Forceps Design with a Parallel Wrist-Gripper Mechanism and Parasitic Motion Compensation. J. Mech. Des. 2022, 144, 063303. [Google Scholar] [CrossRef]
- Li, X.; Qu, H.; Guo, S. Kinematic Performance and Static Analysis of a Two-Degree-of-Freedom 3-RPS/US Parallel Manipulator with Two Passive Limbs. J. Mech. Robot. 2022, 15, 021014. [Google Scholar] [CrossRef]
- Rastegarpanah, A.; Saadat, M.; Borboni, A.; Stolkin, R. Application of a parallel robot in lower limb rehabilitation: A brief capability study. In Proceedings of the 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA), Amritapuri, India, 18–20 December 2016; pp. 1–6. [Google Scholar]
- Zhang, W.; Zhang, W.; Ding, X.; Sun, L. Optimization of the Rotational Asymmetric Parallel Mechanism for Hip Rehabilitation with Force Transmission Factors. J. Mecha. Robot. 2020, 12, 041006. [Google Scholar] [CrossRef]
- Shi, D.; Zhang, W.; Wang, L.; Zhang, W.; Feng, Y.; Ding, X. Joint Angle Adaptive Coordination Control of a Serial-Parallel Lower Limb Rehabilitation Exoskeleton. IEEE Trans. Med. Robot. Bionics 2022, 4, 775–784. [Google Scholar] [CrossRef]
- Ren, B.; Liu, J.; Luo, X.; Chen, J. On the kinematic design of anthropomorphic lower limb exoskeletons and their matching movement. Int. J. Adv. Robot. Syst. 2019, 16, 1–9. [Google Scholar] [CrossRef]
- Song, M.; Guo, S.; Wang, X.; Qu, H. Dynamic analysis and performance verification of a novel hip prosthetic mechanism. Chin. J. Mech. Eng. 2020, 33, 1–17. [Google Scholar] [CrossRef]
- Wang, X.; Guo, S.; Qu, B.; Bai, S. Design and Experimental Verification of a Hip Exoskeleton Based on Human–Machine Dynamics for Walking Assistance. IEEE Trans. Hum.-Mach. Syst. 2023, 53, 85–97. [Google Scholar] [CrossRef]
- Wang, G.; Liu, H.; Deng, P.; Yin, K.; Zhang, G. Dynamic Analysis of 4-SPS/CU Parallel Mechanism Considering Three-Dimensional Wear of Spherical Joint with Clearance. J. Tribol. 2017, 139, 021608. [Google Scholar] [CrossRef]
- Russo, M.; Cafolla, D.; Ceccarelli, M. Design and Experiments of a Novel Humanoid Robot with Parallel Architectures. Robotics 2018, 7, 79. [Google Scholar] [CrossRef]
- Wang, Y.; Mei, Z.; Xu, J.; Zhao, G. Kinematic design of a parallel ankle rehabilitation robot for sprained ankle physiotherapy. In Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guangzhou, China, 11–14 December 2012; pp. 1643–1649. [Google Scholar]
- Saglia, J.A.; Tsagarakis, N.G.; Dai, J.S.; Caldwell, D.G. Control Strategies for Patient-Assisted Training Using the Ankle Rehabilitation Robot (ARBOT). IEEE/ASME Trans. Mechatron. 2013, 18, 1799–1808. [Google Scholar] [CrossRef]
- Wang, C.; Fang, Y.; Guo, S.; Chen, Y. Design and Kinematical Performance Analysis of a 3-RUS/RRR Redundantly Actuated Parallel Mechanism for Ankle Rehabilitation. J. Mechan. Robot. 2013, 5, 041003. [Google Scholar] [CrossRef]
- Jamwal, P.K.; Xie, S.Q.; Hussain, S.; Parsons, J.G. An Adaptive Wearable Parallel Robot for the Treatment of Ankle Injuries. IEEE/ASME Trans. Mechatron. 2014, 19, 64–75. [Google Scholar] [CrossRef]
- Jamwal, P.K.; Hussain, S.; Xie, S.Q. Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm. IEEE Trans. Autom. Sci. Eng. 2015, 12, 1433–1446. [Google Scholar] [CrossRef]
- Vallés, M.; Cazalilla, J.; Valera, Á.; Mata, V.; Page, Á.; Díaz-Rodríguez, M. A 3-PRS parallel manipulator for ankle rehabilitation: Towards a low-cost robotic rehabilitation. Robotica 2015, 35, 1939–1957. [Google Scholar] [CrossRef]
- Jamwal, P.K.; Hussain, S.; Ghayesh, M.H.; Rogozina, S.V. Impedance Control of an Intrinsically Compliant Parallel Ankle Rehabilitation Robot. IEEE Trans. Ind. Electron. 2016, 63, 3638–3647. [Google Scholar] [CrossRef]
- Ruiz-Hidalgo, N.C.; Blanco-Ortega, A.; Abúndez-Pliego, A.; Colín Ocampo, J.; Arias-Montiel, M. Design and Control of a Novel 3-DOF Parallel Robot. In Proceedings of the 2016 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE), Cuernavaca, Mexico, 22-25 November 2016; pp. 66–71. [Google Scholar]
- Azar, W.A.; Akbarimajd, A.; Parvari, E. Intelligent Control Method of a 6-DOF parallel robot Used for Rehabilitation Treatment in lower limbs. Automatika 2016, 57, 466–476. [Google Scholar] [CrossRef]
- Rosado, W.M.A.; Valdés, L.G.V.; Ortega, A. B, Ascencio, J.R.; Beltrán, C.D.G. Passive Rehabilitation Exercises with an Ankle Rehabilitation Prototype Based in a Robot Parallel Structure. IEEE Lat. Am. Trans. 2017, 15, 48–56. [Google Scholar] [CrossRef]
- Rosado, W.M.A.; Ortega, A.B.; Valdés, L.G.V.; Ascencio, J.R.; Beltrán, C.D.G. Active Rehabilitation Exercises with a Parallel Structure Ankle Rehabilitation Prototype. IEEE Lat. Am. Trans. 2017, 15, 786–794. [Google Scholar] [CrossRef]
- Du, Y.; Li, R.; Li, D.; Bai, S. An ankle rehabilitation robot based on 3-RRS spherical parallel mechanism. Adv. Mech. Eng. 2017, 9, 1–8. [Google Scholar] [CrossRef]
- Zhang, M.; Cao, J.; Zhu, G.; Miao, Q.; Zeng, X.; Xie, S.Q. Re configurable workspace and torque capacity of a compliant ankle rehabilitation robot (CARR). Rob. Auton. Syst. 2017, 98, 213–221. [Google Scholar] [CrossRef]
- Jamwal, P.K.; Hussain, S.; Mir-Nasiri, N.; Ghayesh, M.H.; Xie, S.Q. Tele-rehabilitation using in-house wearable ankle rehabilitation robot. Assist. Technol. 2018, 30, 24–33. [Google Scholar] [CrossRef] [PubMed]
- Wang, C.; Wang, L.; Wang, T.; Li, H.; Du, W.; Meng, F.; Zhang, W. Research on an ankle joint auxiliary rehabilitation robot with a rigid-flexible hybrid drive based on a 2-S’PS’ mechanism. Appl. Bionics Biomech. 2019, 2019, 7071064. [Google Scholar] [CrossRef] [PubMed]
- Nurahmi, L.; Gan, D. Reconfiguration of a 3-(rR)PS Metamorphic Parallel Mechanism Based on Complete Workspace and Operation Mode Analysis. J. Mechan. Robot. 2020, 12, 011002. [Google Scholar] [CrossRef]
- Li, J.; Fan, W.; Dong, M.; Rong, X. Research on control strategies for ankle rehabilitation using parallel mechanism. Cogn. Comput. Syst. 2020, 2, 105–111. [Google Scholar] [CrossRef]
- Russo, M.; Ceccarelli, M. Analysis of a wearable robotic system for ankle rehabilitation. Machines 2020, 8, 48. [Google Scholar] [CrossRef]
- Li, J.; Zuo, S.; Zhang, L.; Dong, M.; Zhang, Z.; Tao, C.; Ji, R. Mechanical Design and Performance Analysis of a Novel Parallel Robot for Ankle Rehabilitation. J. Mech. Robot. 2020, 12, 051007. [Google Scholar] [CrossRef]
- Pulloquinga, J.L.; Mata, V.; Valera, Á.; Zamora-Ortiz, P.; Díaz-Rodríguez, M.; Zambrano, I. Experimental analysis of Type II singularities and assembly change points in a 3UPS+RPU parallel robot. Mech. Mach. Theory 2021, 158, 1–27. [Google Scholar] [CrossRef]
- Liu, Y.; Lu, W.; Wu, H.; Xia, Y.; Hu, B.; Zeng, D. Performance analysis and trajectory planning of multi-locomotion mode ankle rehabilitation robot. Rob. Auton. Syst. 2021, 157, 1–11. [Google Scholar] [CrossRef]
- Valencia-Segura, L.E.; Villarreal-Cervantes, M.G.; Corona-Ramírez, L.G.; Cuenca-Jiménez, F.; Muñz-Reina, J.S. Nature-Inspired Intelligent Synthesis of a Spherical Mechanism for Passive Ankle Rehabilitation Using Differential Evolution. IEEE Access 2023, 11, 51331–51352. [Google Scholar] [CrossRef]
- Wu, J.; Liu, Y.; Zhao, J.; Jia, Z. Research on a New Rehabilitation Robot for Balance Disorders. IEEE Trans. Neural Syst. Rehabil. Eng. 2023. [Google Scholar] [CrossRef] [PubMed]
- Shi, M.; Hao, L.; Zhou, Z.; Liu, S.; Han, J.; Yu, N. A Novel Serial-Parallel Hybrid Robot for Rehabilitation Training of Gait and Balance. In Proceedings of the 2023 9th International Conference on Electrical Engineering, Control and Robotics (EECR), Wuhan, China, 24–26 February 2023; pp. 5–10. [Google Scholar]
- Zuo, S.; Li, J.; Dong, M.; Jiao, R.; Wang, S.; Ju, J.; Wang, Y. Design of Composite Parallel External Fixator for Multisegment Foot and Ankle Deformity Correction: A Correction Requirement- Dominated Approach. IEEE/ASME Trans. Mechatron. 2023, 28, 2271–2281. [Google Scholar] [CrossRef]
- Zermane, A.; Guiatni, M.; Alouane, M.A.; Alloun, F.; Tair, M. Optimal Mechatronics Design and Control of a 3-PRS Robotic Platform for Vertigo Diagnosis. In Proceedings of the 2023 International Conference on Control, Automation and Diagnosis (ICCAD), Rome, Italy, 10–12 May 2023; pp. 1–7. [Google Scholar]
- Zhang, J.; Ma, Z.; Wei, J.; Yang, S.; Liu, C.; Guo, S. A Novel Evaluation Index and Optimization Method for Ankle Rehabilitation Robots Based on Ankle-Foot Motion. ASME. J. Biomech. Eng. 2023, 145, 051006. [Google Scholar] [CrossRef] [PubMed]
- Twi-global.Cambridge, UK, 2023. Available online: https://www.twi-global.com/technical-knowledge/faqs/technology-readiness-levels (accessed on 2 July 2023).
- Hanmant, S.; Surendra, T. Magnetorheological Fluids and Its Applications: Current Scenario and Future Prospects. Math. Sci. Int. Res. J. 2021, 6, 207–213. [Google Scholar]
- Mohd, J.; Leary, M.; Subic, A.; Gibson, M. A review of shape memory alloy research, applications and opportunities. Mater. Des. 2014, 56, 1078–1113. [Google Scholar] [CrossRef]
- Chen-Glasser, M.; Li, P.; Ryu, J.; Hong, S. Piezoelectric Materials for Medical Applications. In Piezoelectricity-Organic and Inorganic Materiales and Applications; IntechOpen: London, UK, 2018; Chapter 7; pp. 125–145. ISBN 978-1-78923-647-7. [Google Scholar]
Joints | Movement | Plane | Axis | ROM (o) |
---|---|---|---|---|
Flexion/extension | Sagittal | Frontal | 0–35/0–45 | |
Neck | Right/center bending | Frontal | Sagittal | 0–35/0–45 |
Right/center rotation | Transverse | Vertical | 0–60/0–80 | |
Flexion/extension | Sagittal | Frontal | 0–150/0–170 | |
Shoulder | Abduction/adduction | Frontal | Sagittal | 0–160/0–30 |
Internal/external rotation | Transverse | Transverse | 0–70/0–70 | |
Flexion/extension | Sagittal | Frontal | 0–140/0–10 | |
Hip | Abduction/adduction | Frontal | Sagittal | 0–50/0–30 |
Internal/external Rotation | Transverse | Vertical | 0–40/0–50 | |
Flexion/extension | Sagittal | Frontal | 0–50/0–30 | |
Wrist | Abduction/adduction | Frontal | Sagittal | 0–25/0–30 |
Pronation/supination | Transverse | Vertical | 0–85/0–90 | |
Plantarflexion/dorsiflexion | Sagittal | Frontal | 0–50/0–30 | |
Ankle | Abduction/adduction, | Frontal | Sagittal | 0–10/0–20 |
Inversion/eversion | Transverse | Vertical | 0–60/0–30 |
Country | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
India | 1 | - | - | - | 2 | 3 | 5.9% |
USA | 1 | 2 | 1 | - | - | 4 | 7.8% |
Mexico | 1 | - | - | - | 4 | 5 | 9.8% |
UK | - | 1 | - | 1 | 2 | 4 | 7.8% |
Iran | - | 2 | - | - | 1 | 3 | 5.9% |
Australia | - | 1 | 3 | - | - | 5 | 7.8% |
China | 1 | - | 2 | 3 | 13 | 18 | 37.3% |
Japan | - | - | 1 | - | - | 1 | 2.0% |
Italy | - | - | - | - | 1 | 1 | 2.0% |
Spain | - | - | - | - | 2 | 2 | 3.9% |
Kazakhstan | - | - | - | - | 2 | 2 | 3.9% |
New Zealand | - | - | 1 | - | - | 1 | 2.0% |
Indonesia | - | - | 1 | - | - | 1 | 2.0% |
France | - | - | 1 | - | - | 1 | 2.0% |
Country | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
USA | 2 | 1 | 2 | - | - | 5 | 31.3% |
China | 1 | - | - | 3 | - | 4 | 25.0% |
Japan | - | 2 | - | - | - | 2 | 12.5% |
Italy | - | 1 | - | - | - | 1 | 6.3% |
Mexico | - | 1 | - | - | - | 1 | 6.3% |
South Korea | - | - | 1 | - | - | 1 | 6.3% |
Korea | - | - | 1 | - | - | 1 | 6.3% |
UK | - | - | 1 | - | - | 1 | 6.3% |
Country | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
China | 6 | 6 | 6 | 2 | - | 20 | 76.9% |
France | - | 1 | - | - | - | 1 | 3.8% |
Denmark | - | 1 | - | - | - | 1 | 3.8% |
Mexico | - | - | 1 | - | - | 1 | 3.8% |
UK | - | - | 1 | - | - | 1 | 3.8% |
Turkey | - | - | 1 | - | - | 1 | 3.8% |
Italy | - | - | - | 1 | - | 1 | 3.8% |
TRL | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
TRL 1 | - | - | - | - | - | 0 | 0% |
TRL 2 | - | 3 | - | - | 10 | 13 | 25.49% |
TRL 3 | 2 | 2 | 6 | 2 | 11 | 23 | 45.10% |
TRL 4 | 2 | 1 | 2 | 1 | 9 | 15 | 29.41% |
TRL | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
TRL 1 | - | - | - | - | - | 0 | 0% |
TRL 2 | - | 2 | 1 | 1 | - | 4 | 25.0% |
TRL 3 | 3 | 3 | 4 | 1 | - | 11 | 68.75% |
TRL 4 | - | - | - | 1 | - | 1 | 6.25% |
TRL | Neck | Shoulder | Wrist | Hip | Ankle | Total | Percentage |
---|---|---|---|---|---|---|---|
TRL 1 | 2 | - | - | - | - | 2 | 7.69% |
TRL 2 | 3 | 3 | 4 | 1 | - | 11 | 42.31% |
TRL 3 | 1 | 4 | 5 | 2 | - | 12 | 46.15% |
TRL 4 | - | 1 | - | - | - | 1 | 3.85% |
Joint | DoF | Rehabilitation | Assistance | Humanoids |
---|---|---|---|---|
Neck | 3 | 3-RPS [1], 3-RRR [2], cable-driven [35] | 3-RRS [36], 3-RRR [37], 3-RXS [38] | cable-driven [3,39,41,42,43] |
4 | 4-SPS [4] | - | - | |
2 | - | - | 2-UPUR/RU [55], cable-driven [56] | |
Shoulder | 3 | 5R [44], 3-RSS/S [45], SPM [47], cable-driven [48] | 3-SPS/P [20], 3-RSS/S [46], 3-RRR [19,51], 4B-SPM [52] | 3-RRR [58], 5R [59], cable-driven [35] |
5 | - | - | 5-PMA [54,57] | |
7 | 4B-SPM [49] | cable-driven [50] | cable-driven [53] | |
2 | 3-RPS [61] | 2-UPS/S [68], 2-CSPM [70], cable-driven [72] | 3-4R [74], 2-PUU/RPS [76], cable-driven [9], 3-UPS/S [59], 3-RSR/UUP [78], 3-RPS/US [79] | |
Wrist | 3 | 2-URR/RRS [62], 3-RRR [6], 6-SPS/PS [63], 4-BMA [66,67], cable-driven [65] | 2-RRR [69], 2-RRRPR/RRPR [71] | 3-SPS/S [73] |
4 | - | - | cable-driven [77] | |
5 | - | - | 5-SPM [75] | |
2 | - | 2-UPS+S [85] | 4-SPS/CU [86] | |
Hip | 3 | 2-UPS/RRR [81,82] | 4-RPS [84] | |
4 | - | - | 4-SPS [87] | |
6 | 6-UPS [80] | 6-UPS [83] | - | |
2 | 3-UPS/U [89], 2-RRSP [97,98], 2-SPS [102], 2-UPU/RPU [108], 4-bar [109] | - | - | |
Ankle | 3 | 3-SPS/SP [88], 3-RUS/RRR [90], PMA [91,92,94,101], 3-PRS [93], 3-SPR [95], 3-RRS [99], 4-PMA [100], 3-PSP [15], 3(rR)PS [103], 2-UPS/RRR [14], 2-UPS/RRR [104], cable-driven [105], 2-UPS/RRR [106], 3-RRR [111], 3-PRS [113], 2-UPU/PRPS [114] | - | - |
4 | 3-UPS/RPU [107] | - | - | |
5 | RPUR, SPR [112] | - | - | |
6 | 6-UPS [96] | - | - | |
9 | 6-UPS/3SPR [17], 6-SSP, 3-RPS [110] | - | - |
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Abarca, V.E.; Elias, D.A. A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints. Robotics 2023, 12, 131. https://doi.org/10.3390/robotics12050131
Abarca VE, Elias DA. A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints. Robotics. 2023; 12(5):131. https://doi.org/10.3390/robotics12050131
Chicago/Turabian StyleAbarca, Victoria E., and Dante A. Elias. 2023. "A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints" Robotics 12, no. 5: 131. https://doi.org/10.3390/robotics12050131