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Wearable Electronics for Assessing Human Motor (dis)Abilities
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Wearable Electronics for Assessing Human Motor (dis)Abilities

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 20063

Special Issue Editors

Prof. Dr. Fernanda Irrera

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Guest Editor
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy
Interests: wearable electronics; More-than-Moore integration; nanoelectronics; CMOS device reliability; CMOS image sensors; innovative non-volatile memories
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giovanni Saggio

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Guest Editor
Department of Electronic Engineering, University of Tor Vergata Rome, 00133 Rome, Italy
Interests: wearable sensors; brain–computer interface; motion tracking; gait analysis; sensory glove; biotechnologies
Special Issues, Collections and Topics in MDPI journals
Dr. Vito Errico

E-Mail Website
Guest Editor
Department of Electronic Engineering, University of Tor Vergata Rome, 00133 Rome, Italy
Interests: electronic; nanotechnology; embedded systems; biomedical devices; wireless sensors; body area network
Dr. Ivan Mazzetta

E-Mail Website
Guest Editor
Department of Information Engineering, Electronics and Telecommunication, Sapienza University of Rome, 00184 Rome, Italy
Interests: electromyography; embedded systems; motion analysis; movement analysis; gait analysis; human movement

Special Issue Information

Dear Colleagues,

The study of human postural, gesture, and gait control systems has a great impact in rehabilitation, sports, and medicine, especially for a concrete objective support to the diagnosis and follow-up, related to diseases involving a reduction in balance and motion abilities. 

Such a study can be assessed by electronics, which can play a fundamental role in effectively gathering data later processed by smart algorithms. 

Electronics can implement, among others, electromyography (EMG, to provide information on muscular activity), inertial measurement units (IMU, to supply information on movement, velocity, rotation and orientation of body segments), flex sensors (FS, to determine angular values of human joints), etc., as wearable systems.

In particular, such wearable systems enable wireless body area networks by means of compact integration of sensing, computing and transmission units in a board, together with low-power and energy-harvesting electronic solutions.

Wearable systems can be realized by a unique technology useful for analyzing the locomotion phases, gestures, and postural sway, along with assessment of mass center displacement. Wearable systems can be realized with a fusion of different technologies, too (EMG and/or IMU and/or FS, etc.) for a potentially more effective analysis in terms of pathological disorders classification, enabling a deeper insight into the disorder’s pathophysiology.

Proper electronic treatment of signals, acquired by means of wearable systems, for noise and artifact removal, together with smart algorithms and statistical techniques for data processing and parameter extraction, allows optimum signal representation. The combination of such signals results in a more informative content in that domain for the application at hand. 

Contributions are solicited on new methodologies of human kinematic signal acquisition, signal treatment, and signal combination for practical implementations.

Prof. Dr. Fernanda Irrera
Prof. Dr. Giovanni Saggio
Dr. Vito Errico
Dr. Ivan Mazzetta
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Electromyography
  • Inertial sensors
  • Electronics for sensor fusion
  • Wearable sensor system
  • Analysis of balance and motion ability and disorders

Published Papers (7 papers)

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Research

21 pages, 5120 KiB  
Article
Gait Analyses of Parkinson’s Disease Patients Using Multiscale Entropy
by Yuan-Lun Hsieh and Maysam F. Abbod
Electronics 2021, 10(21), 2604; https://doi.org/10.3390/electronics10212604 - 25 Oct 2021
Cited by 8 | Viewed by 1925
Abstract
Parkinson’s disease (PD) is a type of neurodegenerative diseases. PD influences gait in many aspects: reduced gait speed and step length, increased axial rigidity, and impaired rhythmicity. Gait-related data used in this study are from PhysioNet. Twenty-one PD patients and five healthy controls [...] Read more.
Parkinson’s disease (PD) is a type of neurodegenerative diseases. PD influences gait in many aspects: reduced gait speed and step length, increased axial rigidity, and impaired rhythmicity. Gait-related data used in this study are from PhysioNet. Twenty-one PD patients and five healthy controls (CO) were sorted into four groups: PD without task (PDw), PD with dual task (PDd), control without task (COw), and control with dual task (COd). Since dual task actions are attention demanding, either gait or cognitive function may be affected. To quantify the used walking data, eight pressure sensors installed in each insole are used to measure the vertical ground reaction force. Thus, quantitative measurement analysis is performed utilizing multiscale entropy (MSE) and complexity index (CI) to analyze and differentiate between the ground reaction force of the four different groups. Results show that the CI of patients with PD is higher than that of CO and 11 of the sensor signals are statistically significant (p < 0.05). The COd group has larger CI values at the beginning (p = 0.021) but they get lower at the end of the test (p = 0.000) compared to that in the COw group. The end-of-test CI for the PDw group is lower in one of the feet sensor signals, and in the right total ground reaction force compared to the PDd group counterparts. In conclusion, when people start to adjust their gait due to pathology or stress, CI may increase first and reach a peak, but it decreases afterward when stress or pathology is further increased. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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12 pages, 723 KiB  
Article
Reliability of Recurrence Quantification Analysis Measures for Sit-to-Stand and Stand-to-Sit Activities in Healthy Older Adults Using Wearable Sensors
by Amnah Nasim, David C. Nchekwube and Yoon Sang Kim
Electronics 2021, 10(19), 2438; https://doi.org/10.3390/electronics10192438 - 08 Oct 2021
Cited by 2 | Viewed by 1636
Abstract
Standing up and sitting down are prerequisite motions in most activities of daily living scenarios. The ability to sit down in and stand up from a chair or a bed depreciates and becomes a complex task with increasing age. Hence, research on the [...] Read more.
Standing up and sitting down are prerequisite motions in most activities of daily living scenarios. The ability to sit down in and stand up from a chair or a bed depreciates and becomes a complex task with increasing age. Hence, research on the analysis and recognition of these two activities can help in the design of algorithms for assistive devices. In this work, we propose a reliability analysis for testing the internal consistency of nonlinear recurrence features for sit-to-stand (Si2St) and stand-to-sit (St2Si) activities for motion acceleration data collected by a wearable sensing device for 14 healthy older subjects in the age range of 78 ± 4.9 years. Four recurrence features—%recurrence rate, %determinism, entropy, and average diagonal length—were calculated by using recurrence plots for both activities. A detailed relative and absolute reliability statistical analysis based on Cronbach’s correlation coefficient (α) and standard error of measurement was performed for all recurrence measures. Correlation values as high as α = 0.68 (%determinism) and α = 0.72 (entropy) in the case of Si2St and α = 0.64 (%determinism) and α = 0.69 (entropy) in the case of St2Si—with low standard error in the measurements—show the reliability of %determinism and entropy for repeated acceleration measurements for the characterization of both the St2Si and Si2St activities in the case of healthy older adults. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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16 pages, 42261 KiB  
Article
Concurrent Validation of 3D Joint Angles during Gymnastics Techniques Using Inertial Measurement Units
by Joana Barreto, César Peixoto, Sílvia Cabral, Andrew Mark Williams, Filipe Casanova, Bruno Pedro and António P. Veloso
Electronics 2021, 10(11), 1251; https://doi.org/10.3390/electronics10111251 - 24 May 2021
Cited by 5 | Viewed by 2820
Abstract
There are advantages in using inertial measurement unit systems (IMUS) for biomechanical analysis when compared to 2D/3D video-based analysis. The main advantage is the ability to analyze movement in the natural performance environment, preserving the ecological validity of the task. Coaches can access [...] Read more.
There are advantages in using inertial measurement unit systems (IMUS) for biomechanical analysis when compared to 2D/3D video-based analysis. The main advantage is the ability to analyze movement in the natural performance environment, preserving the ecological validity of the task. Coaches can access accurate and detailed data in real time and use it to optimize feedback and performance. Efforts are needed to validate the accuracy of IMUS. We assess the accuracy of the IMUS Xsens MVN Link system using an optoelectronic system (OS) as a reference when measuring 3D joint angles during the gymnastics round-off back handspring technique. We collected movement kinematics from 10 participants. The coefficient of multiple correlation (CMC) results showed very good and excellent values for the majority of the joint angles, except for neck flexion/extension (F/E). Root mean square errors (RMSE) were below/near 10°, with slightly higher values for shoulder (12.571°), ankle (11.068°), thorax-thigh F/E (21.416°), and thorax–thigh internal/external rotation (I/E) (16.312°). Significant SPM-1D {t} differences for thorax–thigh abduction/adduction (A/A), neck, thorax–thigh, knee, shoulder and ankle F/E were demonstrated during small temporal periods. Our findings suggest that the Xsens MVN Link system provides valid data that can be used to provide feedback in training. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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13 pages, 4575 KiB  
Article
Objective Assessment of Walking Impairments in Myotonic Dystrophy by Means of a Wearable Technology and a Novel Severity Index
by Giovanni Saggio, Alessandro Manoni, Vito Errico, Erica Frezza, Ivan Mazzetta, Rosario Rota, Roberto Massa and Fernanda Irrera
Electronics 2021, 10(6), 708; https://doi.org/10.3390/electronics10060708 - 17 Mar 2021
Cited by 1 | Viewed by 1867
Abstract
Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed [...] Read more.
Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed at objectively evaluating qualitative and quantitative gait alterations. Advantageously, wearable sensing technology has been successfully adopted in objectifying the assessment of motor disabilities in different medical occurrences, so that here we consider the adoption of such technology specifically for DM1. In particular, we measured motor tasks through inertial measurement units on a cohort of 13 DM1 patients and 11 healthy control counterparts. The motor tasks consisted of 16 meters of walking both at a comfortable speed and fast pace. Measured data consisted of plantar-flexion and dorsi-flexion angles assumed by both ankles, so to objectively evidence the footdrop behavior of the DM1 disease, and to define a novel severity index, termed SI-Norm2, to rate the grade of walking impairments. According to the obtained results, our approach could be useful for a more precise stratification of DM1 patients, providing a new tool for a personalized rehabilitation approach. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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15 pages, 3849 KiB  
Article
Assessment of Intuitiveness and Comfort of Wearable Haptic Feedback Strategies for Assisting Level and Stair Walking
by Ilaria Cesini, Giacomo Spigler, Sahana Prasanna, Jessica D’Abbraccio, Daniela De Luca, Filippo Dell’Agnello, Simona Crea, Nicola Vitiello, Alberto Mazzoni and Calogero Maria Oddo
Electronics 2020, 9(10), 1676; https://doi.org/10.3390/electronics9101676 - 14 Oct 2020
Cited by 6 | Viewed by 3274
Abstract
Nowadays, lower-limb prostheses are reaching real-world usability especially on ground-level walking. However, some key tasks such as stair walking are still quite demanding. Providing haptic feedback about the foot placement on the steps might reduce the cognitive load of the task, compensating for [...] Read more.
Nowadays, lower-limb prostheses are reaching real-world usability especially on ground-level walking. However, some key tasks such as stair walking are still quite demanding. Providing haptic feedback about the foot placement on the steps might reduce the cognitive load of the task, compensating for increased dependency on vision and lessen the risk of falling. Experiments on intact subjects can be useful to define the feedback strategies prior to clinical trials, but effective methods to assess the efficacy of the strategies are few and usually rely on the emulation of the disability condition. The present study reports on the design and testing of a wearable haptic feedback system in a protocol involving intact subjects to assess candidate strategies to be adopted in clinical trials. The system integrated a sensorized insole wirelessly connected to a textile waist belt equipped with three vibrating motors. Three stimulation strategies for mapping the insole pressure data to vibrotactile feedback were implemented and compared in terms of intuitiveness and comfort perceived during level and stair walking. The strategies were ranked using a relative rating approach, which highlighted the differences between them and suggested guidelines for their improvement. The feedback evaluation procedure proposed could facilitate the selection and improvement of haptic feedback strategies prior to clinical testing. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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14 pages, 470 KiB  
Article
Smartphone-Based Evaluation of Postural Stability in Parkinson’s Disease Patients During Quiet Stance
by Luigi Borzì, Silvia Fornara, Federica Amato, Gabriella Olmo, Carlo Alberto Artusi and Leonardo Lopiano
Electronics 2020, 9(6), 919; https://doi.org/10.3390/electronics9060919 - 01 Jun 2020
Cited by 10 | Viewed by 2933
Abstract
Background: Postural instability is one of the most troublesome motor symptoms of Parkinson’s Disease (PD). It impairs patients’ quality of life and results in high risk of falls. The aim of this study is to provide a reliable tool for the automated assessment [...] Read more.
Background: Postural instability is one of the most troublesome motor symptoms of Parkinson’s Disease (PD). It impairs patients’ quality of life and results in high risk of falls. The aim of this study is to provide a reliable tool for the automated assessment of postural instability. Methods: Data acquisition was performed on 42 PD patients and 7 young healthy subjects. They were asked to keep a quiet stance position for at least 30 s while wearing a waist-mounted smartphone. A total number of 414 features was extracted from both time and frequency domain, selected based on Pearson’s correlation, and fed to an optimized Support Vector Machine. Results: The implemented model was able to differentiate patients with mild postural instability from those with severe postural instability and from healthy controls, with 100% accuracy. Conclusion: This study demonstrated the feasibility of using inertial sensors embedded in commercial smartphones and proposed a simple protocol for accurate postural instability scoring. This tool can be used for early detection of PD motor signs, disease follow-up and fall prevention. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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15 pages, 4448 KiB  
Article
Assessment of Head Impacts and Muscle Activity in Soccer Using a T3 Inertial Sensor and a Portable Electromyography (EMG) System: A Preliminary Study
by Matthew T. O. Worsey, Bethany S. Jones, Andres Cervantes, Sabrina P. Chauvet, David V. Thiel and Hugo G. Espinosa
Electronics 2020, 9(5), 834; https://doi.org/10.3390/electronics9050834 - 19 May 2020
Cited by 11 | Viewed by 4502
Abstract
Heading the ball is an important skill in soccer. Head impacts are of concern because of the potential adverse health effects. Many elite players now wear GPS (that include inertial monitoring units) on the upper spine for location tracking and workload measurement. By [...] Read more.
Heading the ball is an important skill in soccer. Head impacts are of concern because of the potential adverse health effects. Many elite players now wear GPS (that include inertial monitoring units) on the upper spine for location tracking and workload measurement. By measuring the maximum acceleration of the head and the upper spine, we calculated the acceleration ratio as an attenuation index for participants (n = 8) of different skill levels during a front heading activity. This would allow for in-field estimates of head impacts to be made and concussive events detected. For novice participants, the ratio was as high as 8.3 (mean value 5.0 ± 1.8), whereas, for experienced players, the mean ratio was 3.2 ± 1.5. Elite players stiffen the neck muscles to increase the ball velocity and so the torso acts as a support structure. Electromyography (EMG) signals that were recorded from the neck and shoulder before and after a training intervention showed a major increase in mean average muscle activity (146%, p = 3.39 × 10−6). This was accompanied by a major decrease in acceleration ratio (34.41%, p = 0.008). The average head-ball impact velocity was 1.95 ± 0.53 m/s determined while using optical motion capture. For this low velocity, the impact force was 102 ± 19 N, 13% of the published concussive force. The voluntary action of neck muscles decreases isolated head movements during heading. Coaches and trainers may use this evidence in their development of junior players. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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