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Keywords = hip force sensor

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23 pages, 9777 KB  
Article
Integrated Lower Limb Robotic Orthosis with Embedded Highly Oriented Electrospinning Sensors by Fuzzy Logic-Based Gait Phase Detection and Motion Control
by Ming-Chan Lee, Cheng-Tang Pan, Jhih-Syuan Huang, Zheng-Yu Hoe and Yeong-Maw Hwang
Sensors 2025, 25(5), 1606; https://doi.org/10.3390/s25051606 - 5 Mar 2025
Viewed by 1690
Abstract
This study introduces an integrated lower limb robotic orthosis with near-field electrospinning (NFES) piezoelectric sensors and a fuzzy logic-based gait phase detection system to enhance mobility assistance and rehabilitation. The exoskeleton incorporates embedded pressure sensors within the insoles to capture ground reaction forces [...] Read more.
This study introduces an integrated lower limb robotic orthosis with near-field electrospinning (NFES) piezoelectric sensors and a fuzzy logic-based gait phase detection system to enhance mobility assistance and rehabilitation. The exoskeleton incorporates embedded pressure sensors within the insoles to capture ground reaction forces (GRFs) in real-time. A fuzzy logic inference system processes these signals, classifying gait phases such as stance, initial contact, mid-stance, and pre-swing. The NFES technique enables the fabrication of highly oriented nanofibers, improving sensor sensitivity and reliability. The system employs a master–slave control framework. A Texas Instruments (TI) TMS320F28069 microcontroller (Texas Instruments, Dallas, TX, USA) processes gait data and transmits actuation commands to motors and harmonic drives at the hip and knee joints. The control strategy follows a three-loop methodology, ensuring stable operation. Experimental validation assesses the system’s accuracy under various conditions, including no-load and loaded scenarios. Results demonstrate that the exoskeleton accurately detects gait phases, achieving a maximum tracking error of 4.23% in an 8-s gait cycle under no-load conditions and 4.34% when tested with a 68 kg user. Faster motion cycles introduce a maximum error of 6.79% for a 3-s gait cycle, confirming the system’s adaptability to dynamic walking conditions. These findings highlight the effectiveness of the developed exoskeleton in interpreting human motion intentions, positioning it as a promising solution for wearable rehabilitation and mobility assistance. Full article
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25 pages, 7853 KB  
Article
The Effects of Cross-Legged Sitting on the Lower Limb Muscles and Body Balance and the Implications in Rehabilitation
by Hadeel Alsirhani, Abdullah Alzahrani, Graham Arnold and Weijie Wang
Appl. Sci. 2025, 15(3), 1190; https://doi.org/10.3390/app15031190 - 24 Jan 2025
Viewed by 2928
Abstract
Background: Although a cross-legged sitting (CLS) posture has been commonly practiced as a daily activity, particularly in Arabic, Middle Eastern, and Asian societies, there is no medical study focusing on the effects of cross-legged sitting on body balance and muscular strength. Therefore, this [...] Read more.
Background: Although a cross-legged sitting (CLS) posture has been commonly practiced as a daily activity, particularly in Arabic, Middle Eastern, and Asian societies, there is no medical study focusing on the effects of cross-legged sitting on body balance and muscular strength. Therefore, this study aimed to investigate the effect of CLS on lower extremity muscular strength, muscular electrical activity, and body balance. Methods: Thirty healthy volunteers participated in this research study by performing CLS for a 20 min duration. The balance tests included a static test, i.e., a single-leg-standing posture with eyes closed, to assess if the centre of the pelvis and centre of the shoulders (CoS) moved, and a dynamic test, i.e., four-square-returning, to assess if the moving speed changed. Regarding the muscular assessment, the electrical activity was assessed depending on the maximal value of activation and rooted mean of squared values, while the muscular strength was assessed according to the maximum force by the lower limbs using a force sensor. The balance and muscular results were statistically compared before and after CLS. Results: The duration of the static balance after CLS decreased by an average of 2.5 s, or approximately 15.64%, compared to before CLS (p < 0.05 *). Further, the Centre of Pelvis moved greater distances in the medial–lateral direction after CLS compared to before, but CoS was not significantly changed in the static balance test. However, in the dynamic balance test, the duration significantly decreased by 0.2 s, or approximately 8.5%, after CLS compared to before, meaning that dynamic balance ability improved. Considering the muscle results, only the lateral gastrocnemius muscle was noticeably electrically activated after CLS, while the hip extensor and knee flexor muscles became significantly stronger after CLS compared to before, roughly by about 14%, and the ankle plantar flexor maximum force increased noticeably, by about 4%, after CLS. Conclusions: CLS had a positive impact on the dynamic balance; the strength of the hip extensor, knee flexor, and ankle plantar flexion; and all lower limb muscles, in terms of electrical stimulation, except for the lateral gastrocnemius post-CLS compared to pre-CLS. Therefore, CLS can be safely included in one’s daily routine and in any rehabilitation programme, except for patients who are suffering from static balance disturbance. Although this posture is commonly used in many societies, because this is the first study focused on the impact of CLS on body balance and muscular status, the results would supply knowledge and new understanding, as well as provide clear insight for sitting posture research. Full article
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13 pages, 2712 KB  
Article
External Validation of Accelerometry-Based Mechanical Loading Prediction Equations
by Lucas Veras, Daniela Oliveira, Florêncio Diniz-Sousa, Giorjines Boppre, Ana Resende-Coelho, José Oliveira and Hélder Fonseca
Appl. Sci. 2024, 14(22), 10292; https://doi.org/10.3390/app142210292 - 8 Nov 2024
Viewed by 1092
Abstract
Accurately predicting physical activity-associated mechanical loading is crucial for developing and monitoring exercise interventions that improve bone health. While accelerometer-based prediction equations offer a promising solution, their external validity across different populations and activity contexts remains unclear. This study aimed to validate existing [...] Read more.
Accurately predicting physical activity-associated mechanical loading is crucial for developing and monitoring exercise interventions that improve bone health. While accelerometer-based prediction equations offer a promising solution, their external validity across different populations and activity contexts remains unclear. This study aimed to validate existing mechanical loading prediction equations by applying them to a sample and testing conditions distinct from the original validation studies. A convenience sample of 49 adults performed walking, running, and jumping activities on a force plate while wearing accelerometers at their hip, lower back, and ankle. Peak ground reaction force (pGRF) and peak loading rate (pLR) predictions were assessed for accuracy. Substantial variability in prediction accuracy was found, with pLR showing the highest errors. These findings highlight the need to improve prediction models to account for individual biomechanical differences, sensor placement, and high-impact activities. Such refinements are essential for ensuring the models’ reliability in real-world applications, particularly in clinical and biomechanical research contexts, where accurate assessments of mechanical loading are critical for designing rehabilitation programs, injury prevention strategies, and optimizing bone health interventions. Full article
(This article belongs to the Section Mechanical Engineering)
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14 pages, 2424 KB  
Article
Biomechanical Analysis of Injury Risk in Two High-Altitude Landing Positions Using Xsens Inertial Units and EMG Sensors
by Xuewu Yao, Haojie Li and Chen Xiu
Sensors 2024, 24(21), 6822; https://doi.org/10.3390/s24216822 - 24 Oct 2024
Cited by 1 | Viewed by 2392
Abstract
High-altitude landing maneuvers can pose a significant injury risk, particularly when performed with different landing techniques. This study aims to compare the biomechanical parameters and injury risks associated with two landing positions—staggered foot landing and simultaneous bilateral landing—using Xsens inertial units and electromyography [...] Read more.
High-altitude landing maneuvers can pose a significant injury risk, particularly when performed with different landing techniques. This study aims to compare the biomechanical parameters and injury risks associated with two landing positions—staggered foot landing and simultaneous bilateral landing—using Xsens inertial units and electromyography (EMG) sensors. A total of 26 university students (13 males, 13 females) participated in this study. Kinematic data were collected using inertial measurement units (IMUs), muscle activity was recorded with EMG, and ground reaction forces were captured using 3D force plates. The data were processed and analyzed using the AnyBody modeling system to simulate joint forces, moments, and muscle activation. This study found that simultaneous bilateral landing exhibited greater hip flexion-extension, knee flexion-extension, and ankle inversion. Vertical joint forces were also significantly higher in the hip, knee, and ankle during simultaneous bilateral landing. Staggered foot landing showed higher muscle forces in the gluteus maximus, iliopsoas, and quadriceps femoris (p < 0.001). The EMG analysis revealed significant differences in the biceps femoris (p = 0.008) and quadriceps femoris (p < 0.001). These findings suggest that simultaneous bilateral landing increases joint load, while staggered foot landing increases muscle activation, which may lead to different injury risks between the two techniques. Full article
(This article belongs to the Special Issue IMU and Innovative Sensors for Healthcare)
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23 pages, 7112 KB  
Article
Design and Evaluation of a Novel Variable Stiffness Hip Joint Exoskeleton
by Tao Yang, Chifu Yang, Feng Jiang and Bowen Tian
Sensors 2024, 24(20), 6693; https://doi.org/10.3390/s24206693 - 17 Oct 2024
Viewed by 2236
Abstract
An exoskeleton is a wearable device with human–machine interaction characteristics. An ideal exoskeleton should have kinematic and kinetic characteristics similar to those of the wearer. Most traditional exoskeletons are driven by rigid actuators based on joint torque or position control algorithms. In order [...] Read more.
An exoskeleton is a wearable device with human–machine interaction characteristics. An ideal exoskeleton should have kinematic and kinetic characteristics similar to those of the wearer. Most traditional exoskeletons are driven by rigid actuators based on joint torque or position control algorithms. In order to achieve better human–robot interaction, flexible actuators have been introduced into exoskeletons. However, exoskeletons with fixed stiffness cannot adapt to changing stiffness requirements during assistance. In order to achieve collaborative control of stiffness and torque, a bionic variable stiffness hip joint exoskeleton (BVS-HJE) is designed in this article. The exoskeleton proposed in this article is inspired by the muscles that come in agonist–antagonist pairs, whose actuators are arranged in an antagonistic form on both sides of the hip joint. Compared with other exoskeletons, it has antagonistic actuators with variable stiffness mechanisms, which allow the stiffness control of the exoskeleton joint independent of force (or position) control. A BVS-HJE model was established to study its variable stiffness and static characteristics. Based on the characteristics of the BVS-HJE, a control strategy is proposed that can achieve independent adjustment of joint torque and joint stiffness. In addition, the variable stiffness mechanism can estimate the output force based on the established mathematical model through an encoder, thus eliminating the additional force sensors in the control process. Finally, the variable stiffness properties of the actuator and the controllability of joint stiffness and joint torque were verified through experiments. Full article
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14 pages, 6188 KB  
Article
Monitoring of Hip Joint Forces and Physical Activity after Total Hip Replacement by an Integrated Piezoelectric Element
by Franziska Geiger, Henning Bathel, Sascha Spors, Rainer Bader and Daniel Kluess
Technologies 2024, 12(4), 51; https://doi.org/10.3390/technologies12040051 - 9 Apr 2024
Cited by 4 | Viewed by 3723
Abstract
Resultant hip joint forces can currently only be recorded in situ in a laboratory setting using instrumented total hip replacements (THRs) equipped with strain gauges. However, permanent recording is important for monitoring the structural condition of the implant, for therapeutic purposes, for self-reflection, [...] Read more.
Resultant hip joint forces can currently only be recorded in situ in a laboratory setting using instrumented total hip replacements (THRs) equipped with strain gauges. However, permanent recording is important for monitoring the structural condition of the implant, for therapeutic purposes, for self-reflection, and for research into managing the predicted increasing number of THRs worldwide. Therefore, this study aims to investigate whether a recently proposed THR with an integrated piezoelectric element represents a new possibility for the permanent recording of hip joint forces and the physical activities of the patient. Hip joint forces from nine different daily activities were obtained from the OrthoLoad database and applied to a total hip stem equipped with a piezoelectric element using a uniaxial testing machine. The forces acting on the piezoelectric element were calculated from the generated voltages. The correlation between the calculated forces on the piezoelectric element and the applied forces was investigated, and the regression equations were determined. In addition, the voltage outputs were used to predict the activity with a random forest classifier. The coefficient of determination between the applied maximum forces on the implant and the calculated maximum forces on the piezoelectric element was R2 = 0.97 (p < 0.01). The maximum forces on the THR could be determined via activity-independent determinations with a deviation of 2.49 ± 13.16% and activity-dependent calculation with 0.87 ± 7.28% deviation. The activities could be correctly predicted using the classification model with 95% accuracy. Hence, piezoelectric elements integrated into a total hip stem represent a promising sensor option for the energy-autonomous detection of joint forces and physical activities. Full article
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16 pages, 2977 KB  
Article
Estimation of Muscle Forces of Lower Limbs Based on CNN–LSTM Neural Network and Wearable Sensor System
by Kun Liu, Yong Liu, Shuo Ji, Chi Gao and Jun Fu
Sensors 2024, 24(3), 1032; https://doi.org/10.3390/s24031032 - 5 Feb 2024
Cited by 17 | Viewed by 3647
Abstract
Estimation of vivo muscle forces during human motion is important for understanding human motion control mechanisms and joint mechanics. This paper combined the advantages of the convolutional neural network (CNN) and long-short-term memory (LSTM) and proposed a novel muscle force estimation method based [...] Read more.
Estimation of vivo muscle forces during human motion is important for understanding human motion control mechanisms and joint mechanics. This paper combined the advantages of the convolutional neural network (CNN) and long-short-term memory (LSTM) and proposed a novel muscle force estimation method based on CNN–LSTM. A wearable sensor system was also developed to collect the angles and angular velocities of the hip, knee, and ankle joints in the sagittal plane during walking, and the collected kinematic data were used as the input for the neural network model. In this paper, the muscle forces calculated using OpenSim based on the Static Optimization (SO) method were used as the standard value to train the neural network model. Four lower limb muscles of the left leg, including gluteus maximus (GM), rectus femoris (RF), gastrocnemius (GAST), and soleus (SOL), were selected as the studying objects in this paper. The experiment results showed that compared to the standard CNN and the standard LSTM, the CNN–LSTM performed better in muscle forces estimation under slow (1.2 m/s), medium (1.5 m/s), and fast walking speeds (1.8 m/s). The average correlation coefficients between true and estimated values of four muscle forces under slow, medium, and fast walking speeds were 0.9801, 0.9829, and 0.9809, respectively. The average correlation coefficients had smaller fluctuations under different walking speeds, which indicated that the model had good robustness. The external testing experiment showed that the CNN–LSTM also had good generalization. The model performed well when the estimated object was not included in the training sample. This article proposed a convenient method for estimating muscle forces, which could provide theoretical assistance for the quantitative analysis of human motion and muscle injury. The method has established the relationship between joint kinematic signals and muscle forces during walking based on a neural network model; compared to the SO method to calculate muscle forces in OpenSim, it is more convenient and efficient in clinical analysis or engineering applications. Full article
(This article belongs to the Section Wearables)
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19 pages, 2813 KB  
Article
Effects of Artificially Induced Leg Length Discrepancy on Treadmill-Based Walking and Running Symmetry in Healthy College Students: A Lab-Based Experimental Study
by Maria Korontzi, Ioannis Kafetzakis and Dimitris Mandalidis
Sensors 2023, 23(24), 9695; https://doi.org/10.3390/s23249695 - 8 Dec 2023
Cited by 6 | Viewed by 4495
Abstract
Leg length discrepancy (LLD) is a common postural deviation of musculoskeletal origin, which causes compensatory reactions and often leads to injury. The aim of the study was to investigate the effect of artificially induced LLD on gait symmetry by means of the spatiotemporal [...] Read more.
Leg length discrepancy (LLD) is a common postural deviation of musculoskeletal origin, which causes compensatory reactions and often leads to injury. The aim of the study was to investigate the effect of artificially induced LLD on gait symmetry by means of the spatiotemporal gait parameters and ground reaction forces (GRFs) using a treadmill equipped with capacitive sensors (instrumented) as well as the EMG activity of trunk and hip muscles during walking and running. Twenty-six healthy male and female college students were required to perform two sets of four 2.5-min walking and running trials on an instrumented treadmill at 5.6 and 8.1 km·h−1, respectively, without (0) and with 1, 2, and 3 cm LLD implemented by wearing a special rubber shoe. Statistical analysis was performed using one-way repeated measures or a mixed-design ANOVA. Most spatiotemporal gait parameters and GRFs demonstrated an increase or decrease as LLD increased either on the short-limb or the long-limb side, with changes becoming more apparent at ≥1 cm LLD during walking and ≥2 cm LLD during running. The EMG activity of trunk and hip muscles was not affected by LLD. Our findings showed that gait symmetry in terms of treadmill-based spatiotemporal parameters of gait and GRFs is affected by LLD, the magnitude of which depends on the speed of locomotion. Full article
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17 pages, 3835 KB  
Article
Examining Gait Characteristics in People with Osteoporosis Utilizing a Non-Wheeled Smart Walker through Spatiotemporal Analysis
by Nazia Ejaz, Saad Jawaid Khan, Fahad Azim, Mehwish Faiz, Emil Teuțan, Alin Pleșa, Alexandru Ianosi-Andreeva-Dimitrova and Sergiu-Dan Stan
Appl. Sci. 2023, 13(21), 12017; https://doi.org/10.3390/app132112017 - 3 Nov 2023
Cited by 2 | Viewed by 2544
Abstract
Fragility fractures, caused by low-energy trauma, are a significant global health concern, with 158 million people aged 50 and over at risk. Hip fractures, a common issue in elderly patients, are often linked to underlying conditions such as osteoporosis. This study proposed a [...] Read more.
Fragility fractures, caused by low-energy trauma, are a significant global health concern, with 158 million people aged 50 and over at risk. Hip fractures, a common issue in elderly patients, are often linked to underlying conditions such as osteoporosis. This study proposed a cost-effective solution using a non-wheeled smart walker with load sensors to measure gait parameters, addressing the high cost of traditional gait analysis equipment, the prototype used PASCO load cells PS2200 for force measurement, eliminating the need for Arduino UNO or microcontroller-based hardware. A lightweight amplifier PS2198 amplified the signal, which was transmitted via USB to a personal computer. PASCO capstone software was used for data recording and visualization. The smart walker was tested on forty volunteers divided into two equal groups: those with osteoporosis and those without, by performing a 10 m walk test three times. ANOVA comparing spatiotemporal parameters (TSPs) of the two participant groups (α = 0.05) showed that significant differences lay in terms of time taken to complete the walk test (p < 0.01), left step length (p = 0.03), walking speed (p = 0.02), and stride length (p < 0.02). The results indicate that this smart walker is a reliable tool for assessing gait patterns in individuals with osteoporosis. The proposed system can be an alternative for time consuming and costly methods such as motion capture, and for socially stigmatizing devices such as exoskeletons. It can also be used further to identify risk factors of osteoporosis. Full article
(This article belongs to the Special Issue Mechatronics System Design in Medical Engineering)
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22 pages, 41837 KB  
Article
Design, Control, and Validation of a Symmetrical Hip and Straight-Legged Vertically-Compliant Bipedal Robot
by Jun Tang, Yudi Zhu, Wencong Gan, Haiming Mou, Jie Leng, Qingdu Li, Zhiqiang Yu and Jianwei Zhang
Biomimetics 2023, 8(4), 340; https://doi.org/10.3390/biomimetics8040340 - 1 Aug 2023
Cited by 4 | Viewed by 3361
Abstract
This paper presents the development, modeling, and control of L03, an underactuated 3D bipedal robot with symmetrical hips and straight legs. This innovative design requires only five actuators, two for the legs and three for the hips. This paper is divided into three [...] Read more.
This paper presents the development, modeling, and control of L03, an underactuated 3D bipedal robot with symmetrical hips and straight legs. This innovative design requires only five actuators, two for the legs and three for the hips. This paper is divided into three parts: (1) mechanism design and kinematic analysis; (2) trajectory planning for the center of mass and foot landing points based on the Divergent Component of Motion (DCM), enabling lateral and forward walking capabilities for the robot; and (3) gait stability analysis through prototype experiments. The primary focus of this study is to explore the application of underactuated symmetrical designs and determine the number of motors required to achieve omnidirectional movement of a bipedal robot. Our simulation and experimental results demonstrate that L03 achieves simple walking with a stable and consistent gait. Due to its lightweight construction, low leg inertia, and straight-legged design, L03 can achieve ground perception and gentle ground contact without the need for force sensors. Compared to existing bipedal robots, L03 closely adheres to the characteristics of the linear inverted pendulum model, making it an invaluable platform for future algorithm research. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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17 pages, 8831 KB  
Article
A Transformer-Based Neural Network for Gait Prediction in Lower Limb Exoskeleton Robots Using Plantar Force
by Jiale Ren, Aihui Wang, Hengyi Li, Xuebin Yue and Lin Meng
Sensors 2023, 23(14), 6547; https://doi.org/10.3390/s23146547 - 20 Jul 2023
Cited by 15 | Viewed by 3658
Abstract
Lower limb exoskeleton robots have shown significant research value due to their capabilities of providing assistance to wearers and improving physical motion functions. As a type of robotic technology, wearable robots are directly in contact with the wearer’s limbs during operation, necessitating a [...] Read more.
Lower limb exoskeleton robots have shown significant research value due to their capabilities of providing assistance to wearers and improving physical motion functions. As a type of robotic technology, wearable robots are directly in contact with the wearer’s limbs during operation, necessitating a high level of human–robot collaboration to ensure safety and efficacy. Furthermore, gait prediction for the wearer, which helps to compensate for sensor delays and provide references for controller design, is crucial for improving the the human–robot collaboration capability. For gait prediction, the plantar force intrinsically reflects crucial gait patterns regardless of individual differences. To be exact, the plantar force encompasses a doubled three-axis force, which varies over time concerning the two feet, which also reflects the gait patterns indistinctly. In this paper, we developed a transformer-based neural network (TFSformer) comprising convolution and variational mode decomposition (VMD) to predict bilateral hip and knee joint angles utilizing the plantar pressure. Given the distinct information contained in the temporal and the force-space dimensions of plantar pressure, the encoder uses 1D convolution to obtain the integrated features in the two dimensions. As for the decoder, it utilizes a multi-channel attention mechanism to simultaneously focus on both dimensions and a deep multi-channel attention structure to reduce the computational and memory consumption. Furthermore, VMD is applied to networks to better distinguish the trends and changes in data. The model is trained and tested on a self-constructed dataset that consists of data from 35 volunteers. The experimental results show that FTSformer reduces the mean absolute error (MAE) up to 10.83%, 15.04% and 8.05% and the mean squared error (MSE) by 20.40%, 29.90% and 12.60% compared to the CNN model, the transformer model and the CNN transformer model, respectively. Full article
(This article belongs to the Topic Human Movement Analysis)
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13 pages, 2201 KB  
Article
Hip Joint Angles and Moments during Stair Ascent Using Neural Networks and Wearable Sensors
by Megan V. McCabe, Douglas W. Van Citters and Ryan M. Chapman
Bioengineering 2023, 10(7), 784; https://doi.org/10.3390/bioengineering10070784 - 30 Jun 2023
Cited by 9 | Viewed by 3933
Abstract
End-stage hip joint osteoarthritis treatment, known as total hip arthroplasty (THA), improves satisfaction, life quality, and activities of daily living (ADL) function. Postoperatively, evaluating how patients move (i.e., their kinematics/kinetics) during ADL often requires visits to clinics or specialized biomechanics laboratories. Prior work [...] Read more.
End-stage hip joint osteoarthritis treatment, known as total hip arthroplasty (THA), improves satisfaction, life quality, and activities of daily living (ADL) function. Postoperatively, evaluating how patients move (i.e., their kinematics/kinetics) during ADL often requires visits to clinics or specialized biomechanics laboratories. Prior work in our lab and others have leveraged wearables and machine learning approaches such as artificial neural networks (ANNs) to quantify hip angles/moments during simple ADL such as walking. Although level-ground ambulation is necessary for patient satisfaction and post-THA function, other tasks such as stair ascent may be more critical for improvement. This study utilized wearable sensors/ANNs to quantify sagittal/frontal plane angles and moments of the hip joint during stair ascent from 17 healthy subjects. Shin/thigh-mounted inertial measurement units and force insole data were inputted to an ANN (2 hidden layers, 10 total nodes). These results were compared to gold-standard optical motion capture and force-measuring insoles. The wearable-ANN approach performed well, achieving rRMSE = 17.7% and R2 = 0.77 (sagittal angle/moment: rRMSE = 17.7 ± 1.2%/14.1 ± 0.80%, R2 = 0.80 ± 0.02/0.77 ± 0.02; frontal angle/moment: rRMSE = 26.4 ± 1.4%/12.7 ± 1.1%, R2 = 0.59 ± 0.02/0.93 ± 0.01). While we only evaluated healthy subjects herein, this approach is simple and human-centered and could provide portable technology for quantifying patient hip biomechanics in future investigations. Full article
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11 pages, 1367 KB  
Article
Electromyographic and Stabilometric Analysis of the Static and Dynamic “Standing Bird Dog” Exercise
by Raffaele Losavio, Samuele Contemori, Stefano Bartoli, Cristina V. Dieni, Roberto Panichi and Andrea Biscarini
Sports 2023, 11(6), 119; https://doi.org/10.3390/sports11060119 - 16 Jun 2023
Cited by 2 | Viewed by 6549
Abstract
(1) Background: The “bird dog” exercise is considered one of the most effective therapeutic exercises for lumbopelvic rehabilitation and the prevention and treatment of low back pain. The “standing bird dog” (SBD) exercise, executed in a single-leg stance, constitutes a natural and challenging [...] Read more.
(1) Background: The “bird dog” exercise is considered one of the most effective therapeutic exercises for lumbopelvic rehabilitation and the prevention and treatment of low back pain. The “standing bird dog” (SBD) exercise, executed in a single-leg stance, constitutes a natural and challenging variation in the “bird dog”; nevertheless, this exercise has not yet been investigated. This study provides a stabilometric and electromyographic analysis of the SBD performed in static and dynamic conditions and in ipsilateral and contralateral variations; (2) Methods: A time-synchronized motion capture system, wireless electromyography sensors, and triaxial force platform were used to analyze the selected SBD exercises; (3) Results: In dynamic conditions, the gluteus maximum, multifidus, lumbar erector spinae, and gluteus medius reached a mean activation level higher than in the static condition, with peak activation levels of 80%, 60%, 55%, and a 45% maximum voluntary isometric contraction, respectively. In the static condition, balance control was more challenging in the mediolateral compared to the anteroposterior direction. In the dynamic condition, the balance challenge was higher in the anteroposterior direction and higher than the static condition in both directions; (4) Conclusions: The SBD was proved to be effective for strengthening the hip and lumbar extensor muscles and provided a powerful challenge to single-leg balance control in both mediolateral and anteroposterior directions. Full article
(This article belongs to the Special Issue Biomechanics and Sports Performances)
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15 pages, 2029 KB  
Article
Smartphone Technology to Remotely Measure Postural Sway during Double- and Single-Leg Squats in Adults with Femoroacetabular Impingement and Those with No Hip Pain
by Charlotte J. Marshall, Charlotte Ganderton, Adam Feltham, Doa El-Ansary, Adrian Pranata, John O’Donnell, Amir Takla, Phong Tran, Nilmini Wickramasinghe and Oren Tirosh
Sensors 2023, 23(11), 5101; https://doi.org/10.3390/s23115101 - 26 May 2023
Cited by 6 | Viewed by 3309
Abstract
Background: The COVID-19 pandemic has accelerated the demand for utilising telehealth as a major mode of healthcare delivery, with increasing interest in the use of tele-platforms for remote patient assessment. In this context, the use of smartphone technology to measure squat performance in [...] Read more.
Background: The COVID-19 pandemic has accelerated the demand for utilising telehealth as a major mode of healthcare delivery, with increasing interest in the use of tele-platforms for remote patient assessment. In this context, the use of smartphone technology to measure squat performance in people with and without femoroacetabular impingement (FAI) syndrome has not been reported yet. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient’s device and measure their squat performance in real time using the smartphone inertial sensors. The aim of this study was to investigate the association and test–retest reliability of the TelePhysio app in measuring postural sway performance during a double-leg (DLS) and single-leg (SLS) squat task. In addition, the study investigated the ability of TelePhysio to detect differences in DLS and SLS performance between people with FAI and without hip pain. Methods: A total of 30 healthy (nfemales = 12) young adults and 10 adults (nfemales = 2) with diagnosed FAI syndrome participated in the study. Healthy participants performed DLS and SLS on force plates in our laboratory, and remotely in their homes using the TelePhysio smartphone application. Sway measurements were compared using the centre of pressure (CoP) and smartphone inertial sensor data. A total of 10 participants with FAI (nfemales = 2) performed the squat assessments remotely. Four sway measurements in each axis (x, y, and z) were computed from the TelePhysio inertial sensors: (1) average acceleration magnitude from the mean (aam), (2) root-mean-square acceleration (rms), (3) range acceleration (r), and (4) approximate entropy (apen), with lower values indicating that the movement is more regular, repetitive, and predictable. Differences in TelePhysio squat sway data were compared between DLS and SLS, and between healthy and FAI adults, using analysis of variance with significance set at 0.05. Results: The TelePhysio aam measurements on the x- and y-axes had significant large correlations with the CoP measurements (r = 0.56 and r = 0.71, respectively). The TelePhysio aam measurements demonstrated moderate to substantial between-session reliability values of 0.73 (95% CI 0.62–0.81), 0.85 (95% CI 0.79–0.91), and 0.73 (95% CI 0.62–0.82) for aamx, aamy, and aamz, respectively. The DLS of the FAI participants showed significantly lower aam and apen values in the medio-lateral direction compared to the healthy DLS, healthy SLS, and FAI SLS groups (aam = 0.13, 0.19, 0.29, and 0.29, respectively; and apen = 0.33, 0.45, 0.52, and 0.48, respectively). In the anterior–posterior direction, healthy DLS showed significantly greater aam values compared to the healthy SLS, FAI DLS, and FAI SLS groups (1.26, 0.61, 0.68, and 0.35, respectively). Conclusions: The TelePhysio app is a valid and reliable method of measuring postural control during DLS and SLS tasks. The application is capable of distinguishing performance levels between DLS and SLS tasks, and between healthy and FAI young adults. The DLS task is sufficient to distinguish the level of performance between healthy and FAI adults. This study validates the use of smartphone technology as a tele-assessment clinical tool for remote squat assessment. Full article
(This article belongs to the Special Issue Wearables Technology for COVID-19)
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16 pages, 4819 KB  
Article
Center of Mass Estimation Using a Force Platform and Inertial Sensors for Balance Evaluation in Quiet Standing
by Motomichi Sonobe and Yoshio Inoue
Sensors 2023, 23(10), 4933; https://doi.org/10.3390/s23104933 - 20 May 2023
Cited by 10 | Viewed by 5208
Abstract
Accurate estimation of the center of mass is necessary for evaluating balance control during quiet standing. However, no practical center of mass estimation method exists because of problems with estimation accuracy and theoretical validity in previous studies that used force platforms or inertial [...] Read more.
Accurate estimation of the center of mass is necessary for evaluating balance control during quiet standing. However, no practical center of mass estimation method exists because of problems with estimation accuracy and theoretical validity in previous studies that used force platforms or inertial sensors. This study aimed to develop a method for estimating the center of mass displacement and velocity based on equations of motion describing the standing human body. This method uses a force platform under the feet and an inertial sensor on the head and is applicable when the support surface moves horizontally. We compared the center of mass estimation accuracy of the proposed method with those of other methods in previous studies using estimates from the optical motion capture system as the true value. The results indicate that the present method has high accuracy in quiet standing, ankle motion, hip motion, and support surface swaying in anteroposterior and mediolateral directions. The present method could help researchers and clinicians to develop more accurate and effective balance evaluation methods. Full article
(This article belongs to the Collection Medical Applications of Sensor Systems and Devices)
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