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Wearable Sensors for Biomechanics Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 62078

Special Issue Editor

School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong 2522, Australia
Interests: rehabilitation engineering; technology for elderly people; human movement; postural control; prosthetics; orthotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of wearable sensors in measuring force and motions of human structures can potentially bring benefits to health care, sport, and well-being. Examples of wearable sensors for biomechanical measurements include accelerometers, gyroscopes, magnetometers, ultrasound, optical, nanomaterial-based, EMG, and force sensors.

This Special Issue focuses on applications of wearable sensors in these three areas:
Rehabilitation and gerontology
Sport performance and injury prevention
Risk assessment at work

Papers that look into developments, uses, and/or outcome measurement of wearable sensors in the above three areas are welcomed. Original research and review papers in these areas are encouraged.

Prof. Dr. Winson Lee
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • Wearable Sensors
  • Wearable Smart Devices
  • Accelerometers
  • Gyroscopes
  • Magnetometers
  • Ultrasound Optical
  • Nanomaterial-Based
  • EMG and force sensors
  • Exoskeletons
  • Soft Wearable robotics

Related Special Issue

Published Papers (24 papers)

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Research

14 pages, 4970 KiB  
Article
Characterizing Bodyweight-Supported Treadmill Walking on Land and Underwater Using Foot-Worn Inertial Measurement Units and Machine Learning for Gait Event Detection
by Seongmi Song, Nathaniel J. Fernandes and Andrew D. Nordin
Sensors 2023, 23(18), 7945; https://doi.org/10.3390/s23187945 - 17 Sep 2023
Viewed by 1074
Abstract
Gait rehabilitation commonly relies on bodyweight unloading mechanisms, such as overhead mechanical support and underwater buoyancy. Lightweight and wireless inertial measurement unit (IMU) sensors provide a cost-effective tool for quantifying body segment motions without the need for video recordings or ground reaction force [...] Read more.
Gait rehabilitation commonly relies on bodyweight unloading mechanisms, such as overhead mechanical support and underwater buoyancy. Lightweight and wireless inertial measurement unit (IMU) sensors provide a cost-effective tool for quantifying body segment motions without the need for video recordings or ground reaction force measures. Identifying the instant when the foot contacts and leaves the ground from IMU data can be challenging, often requiring scrupulous parameter selection and researcher supervision. We aimed to assess the use of machine learning methods for gait event detection based on features from foot segment rotational velocity using foot-worn IMU sensors during bodyweight-supported treadmill walking on land and underwater. Twelve healthy subjects completed on-land treadmill walking with overhead mechanical bodyweight support, and three subjects completed underwater treadmill walking. We placed IMU sensors on the foot and recorded motion capture and ground reaction force data on land and recorded IMU sensor data from wireless foot pressure insoles underwater. To detect gait events based on IMU data features, we used random forest machine learning classification. We achieved high gait event detection accuracy (95–96%) during on-land bodyweight-supported treadmill walking across a range of gait speeds and bodyweight support levels. Due to biomechanical changes during underwater treadmill walking compared to on land, accurate underwater gait event detection required specific underwater training data. Using single-axis IMU data and machine learning classification, we were able to effectively identify gait events during bodyweight-supported treadmill walking on land and underwater. Robust and automated gait event detection methods can enable advances in gait rehabilitation. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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20 pages, 5115 KiB  
Article
Unsupervised Gait Event Identification with a Single Wearable Accelerometer and/or Gyroscope: A Comparison of Methods across Running Speeds, Surfaces, and Foot Strike Patterns
by Dovin Kiernan, Kristine Dunn Siino and David A. Hawkins
Sensors 2023, 23(11), 5022; https://doi.org/10.3390/s23115022 - 24 May 2023
Cited by 5 | Viewed by 1669
Abstract
We evaluated 18 methods capable of identifying initial contact (IC) and terminal contact (TC) gait events during human running using data from a single wearable sensor on the shank or sacrum. We adapted or created code to automatically execute each method, then applied [...] Read more.
We evaluated 18 methods capable of identifying initial contact (IC) and terminal contact (TC) gait events during human running using data from a single wearable sensor on the shank or sacrum. We adapted or created code to automatically execute each method, then applied it to identify gait events from 74 runners across different foot strike angles, surfaces, and speeds. To quantify error, estimated gait events were compared to ground truth events from a time-synchronized force plate. Based on our findings, to identify gait events with a wearable on the shank, we recommend the Purcell or Fadillioglu method for IC (biases +17.4 and −24.3 ms; LOAs −96.8 to +131.6 and −137.0 to +88.4 ms) and the Purcell method for TC (bias +3.5 ms; LOAs −143.9 to +150.9 ms). To identify gait events with a wearable on the sacrum, we recommend the Auvinet or Reenalda method for IC (biases −30.4 and +29.0 ms; LOAs −149.2 to +88.5 and −83.3 to +141.3 ms) and the Auvinet method for TC (bias −2.8 ms; LOAs −152.7 to +147.2 ms). Finally, to identify the foot in contact with the ground when using a wearable on the sacrum, we recommend the Lee method (81.9% accuracy). Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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9 pages, 2206 KiB  
Communication
Correlation of Acceleration Curves in Gravitational Direction for Different Body Segments during High-Impact Jumping Exercises
by Lukas Reinker, Dominic Bläsing, Rudolf Bierl, Sabina Ulbricht and Sebastian Dendorfer
Sensors 2023, 23(4), 2276; https://doi.org/10.3390/s23042276 - 17 Feb 2023
Viewed by 1285
Abstract
Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy [...] Read more.
Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy phases or preventive exercise programs in everyday life. This study aimed to determine the accuracy and reliability of measured acceleration data at different body positions compared to accelerations at the pelvis during different jumping exercises. Accelerations at the hips have been investigated in previous studies with regard to osteoporosis prevention. Data were collected using an IMU-based motion capture system (Xsens) consisting of 17 sensors. Forty-nine subjects were included in this study. The analysis shows the correlation between impacts and the corresponding drop height, which are dependent on the respective exercise. Very high correlations (0.83–0.94) were found between accelerations at the pelvis and the other measured segments at the upper body. The foot sensors provided very weak correlations (0.20–0.27). Accelerations measured at the pelvis during jumping exercises can be tracked very well on the upper body and upper extremities, including locations where smart devices are typically worn, which gives possibilities for remote and continuous monitoring of programs. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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17 pages, 4595 KiB  
Article
Machine-Learning-Based Methodology for Estimation of Shoulder Load in Wheelchair-Related Activities Using Wearables
by Sabrina Amrein, Charlotte Werner, Ursina Arnet and Wiebe H. K. de Vries
Sensors 2023, 23(3), 1577; https://doi.org/10.3390/s23031577 - 01 Feb 2023
Cited by 3 | Viewed by 2051
Abstract
There is a high prevalence of shoulder problems in manual wheelchair users (MWUs) with a spinal cord injury. How shoulder load relates to shoulder problems remains unclear. This study aimed to develop a machine-learning-based methodology to estimate the shoulder load in wheelchair-related activities [...] Read more.
There is a high prevalence of shoulder problems in manual wheelchair users (MWUs) with a spinal cord injury. How shoulder load relates to shoulder problems remains unclear. This study aimed to develop a machine-learning-based methodology to estimate the shoulder load in wheelchair-related activities of daily living using wearable sensors. Ten able-bodied participants equipped with five inertial measurement units (IMU) on their thorax, right arm, and wheelchair performed activities exemplary of daily life of MWUs. Electromyography (EMG) was recorded from the long head of the biceps and medial part of the deltoid. A neural network was trained to predict the shoulder load based on IMU and EMG data. Different cross-validation strategies, sensor setups, and model architectures were examined. The predicted shoulder load was compared to the shoulder load determined with musculoskeletal modeling. A subject-specific biLSTM model trained on a sparse sensor setup yielded the most promising results (mean correlation coefficient = 0.74 ± 0.14, relative root-mean-squared error = 8.93% ± 2.49%). The shoulder-load profiles had a mean similarity of 0.84 ± 0.10 over all activities. This study demonstrates the feasibility of using wearable sensors and neural networks to estimate the shoulder load in wheelchair-related activities of daily living. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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15 pages, 2139 KiB  
Article
Field-Based Biomechanical Assessment of the Snatch in Olympic Weightlifting Using Wearable In-Shoe Sensors and Videos—A Preliminary Report
by Cheng Loong Ang and Pui Wah Kong
Sensors 2023, 23(3), 1171; https://doi.org/10.3390/s23031171 - 19 Jan 2023
Viewed by 3363
Abstract
Traditionally, the biomechanical analysis of Olympic weightlifting movements required laboratory equipment such as force platforms and transducers, but such methods are difficult to implement in practice. This study developed a field-based method using wearable technology and videos for the biomechanical assessment of weightlifters. [...] Read more.
Traditionally, the biomechanical analysis of Olympic weightlifting movements required laboratory equipment such as force platforms and transducers, but such methods are difficult to implement in practice. This study developed a field-based method using wearable technology and videos for the biomechanical assessment of weightlifters. To demonstrate the practicality of our method, we collected kinetic and kinematic data on six Singapore National Olympic Weightlifters. The participants performed snatches at 80% to 90% of their competition one-repetition maximum, and the three best attempts were used for the analysis. They wore a pair of in-shoe force sensors loadsol® (novel, Munich, Germany) to measure the vertical ground reaction forces under each foot. Concurrently, a video camera recorded the barbell movement from the side. The kinematics (e.g., trajectories and velocities) of the barbell were extracted using a free video analysis software (Kinovea). The power–time history was calculated from the force and velocity data. The results showed differences in power, force, and barbell velocity with moderate to almost perfect reliability. Technical inconsistency in the barbell trajectories were also identified. In conclusion, this study presented a simple and practical approach to evaluating weightlifters using in-shoe wearable sensors and videos. Such information can be useful for monitoring progress, identifying errors, and guiding training plans for weightlifters. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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13 pages, 2502 KiB  
Article
The Effect of Key Anthropometric and Biomechanics Variables Affecting the Lower Back Forces of Healthcare Workers
by Xiaoxu Ji, Alexa Littman, Ranuki Onara Hettiarachchige and Davide Piovesan
Sensors 2023, 23(2), 658; https://doi.org/10.3390/s23020658 - 06 Jan 2023
Cited by 6 | Viewed by 1276
Abstract
Wearable devices are becoming ubiquitous and can be used to better estimate postures and movements to reduce the risk of injuries. Thirty-three participants were recruited in this study to perform two daily repetitive patient transfer tasks while the full body movements were acquired [...] Read more.
Wearable devices are becoming ubiquitous and can be used to better estimate postures and movements to reduce the risk of injuries. Thirty-three participants were recruited in this study to perform two daily repetitive patient transfer tasks while the full body movements were acquired using a set of magneto-inertial wearable devices. The use of wearable devices allowed for the estimation of the forces provoked on the lower back during the entire task performance. In postures where the forces exceeded the warning threshold found in the literature, healthcare workers were considered to have a greater risk of injury. Additionally, the maximum force exerted by each hand to avoid injury to the spinal column was also estimated. Knowing the key anthropometric variables associated with musculoskeletal disorders (MSDs) will enable engineers and researchers to design better assistive devices and injury prevention programs in diverse workplaces. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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13 pages, 1734 KiB  
Article
The Effect of the Weight and Type of Equipment on Shoulder and Back Muscle Activity in Surface Electromyography during the Overhead Press—Preliminary Report
by Michalina Błażkiewicz and Anna Hadamus
Sensors 2022, 22(24), 9762; https://doi.org/10.3390/s22249762 - 13 Dec 2022
Cited by 1 | Viewed by 2709
Abstract
The overhead press is a multi-joint exercise that has the potential to use a high external load due to the cooperation of many muscle groups. The purpose of this study was to compare the activity of shoulder and back muscles during the overhead [...] Read more.
The overhead press is a multi-joint exercise that has the potential to use a high external load due to the cooperation of many muscle groups. The purpose of this study was to compare the activity of shoulder and back muscles during the overhead press with a kettlebell and a dumbbell. Surface electromyography (EMG) for the anterior and posterior deltoid, upper and lower trapezius, serratus anterior, and spinal erectors was analysed for 20 subjects. Participants performed the four trials of pressing kettlebell and dumbbell, weighted at 6 kg, and 70% of one maximum repetition (1RM) in the sitting position. Statistical analysis was performed using a non-parametric Friedman test and a post-hoc test of Dunn Bonferroni. No significant differences were found in the activation of assessed muscles when comparing dumbbell to kettlebell press trials with the same load (6 kg and 70% of 1RM). However, muscle activity of all muscles except the upper trapezius was always higher for kettlebell pressing. Different center of gravity locations in the kettlebell versus the dumbbell can increase shoulder muscle activity during the overhead press. However, more studies are required to confirm these results. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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11 pages, 1754 KiB  
Article
Scoring the Sit-to-Stand Performance of Parkinson’s Patients with a Single Wearable Sensor
by Frédéric Marin, Elke Warmerdam, Zoé Marin, Khalil Ben Mansour, Walter Maetzler and Clint Hansen
Sensors 2022, 22(21), 8340; https://doi.org/10.3390/s22218340 - 30 Oct 2022
Cited by 1 | Viewed by 1503
Abstract
Monitoring disease progression in Parkinson’s disease is challenging. Postural transfers by sit-to-stand motions are adapted to trace the motor performance of subjects. Wearable sensors such as inertial measurement units allow for monitoring motion performance. We propose quantifying the sit-to-stand performance based on two [...] Read more.
Monitoring disease progression in Parkinson’s disease is challenging. Postural transfers by sit-to-stand motions are adapted to trace the motor performance of subjects. Wearable sensors such as inertial measurement units allow for monitoring motion performance. We propose quantifying the sit-to-stand performance based on two scores compiling kinematics, dynamics, and energy-related variables. Three groups participated in this research: asymptomatic young participants (n = 33), senior asymptomatic participants (n = 17), and Parkinson’s patients (n = 20). An unsupervised classification was performed of the two scores to differentiate the three populations. We found a sensitivity of 0.4 and a specificity of 0.96 to distinguish Parkinson’s patients from asymptomatic subjects. In addition, seven Parkinson’s patients performed the sit-to-stand task “ON” and “OFF” medication, and we noted the scores improved with the patients’ medication states (MDS-UPDRS III scores). Our investigation revealed that Parkinson’s patients demonstrate a wide spectrum of mobility variations, and while one inertial measurement unit can quantify the sit-to-stand performance, differentiating between PD patients and healthy adults and distinguishing between “ON” and “OFF” periods in PD patients is still challenging. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 2571 KiB  
Article
Power Spectrum of Acceleration and Angular Velocity Signals as Indicators of Muscle Fatigue during Upper Limb Low-Load Repetitive Tasks
by Béatrice Moyen-Sylvestre, Étienne Goubault, Mickaël Begon, Julie N. Côté, Jason Bouffard and Fabien Dal Maso
Sensors 2022, 22(20), 8008; https://doi.org/10.3390/s22208008 - 20 Oct 2022
Cited by 4 | Viewed by 1637
Abstract
Muscle fatigue is a risk factor for developing musculoskeletal disorders during low-load repetitive tasks. The objective of this study was to assess the effect of muscle fatigue on power spectrum changes of upper limb and trunk acceleration and angular velocity during a repetitive [...] Read more.
Muscle fatigue is a risk factor for developing musculoskeletal disorders during low-load repetitive tasks. The objective of this study was to assess the effect of muscle fatigue on power spectrum changes of upper limb and trunk acceleration and angular velocity during a repetitive pointing task (RPT) and a work task. Twenty-four participants equipped with 11 inertial measurement units, that include acceleration and gyroscope sensors, performed a tea bag filling work task before and immediately after a fatiguing RPT. During the RPT, the power spectrum of acceleration and angular velocity increased in the movement and in 6–12 Hz frequency bands for sensors positioned on the head, sternum, and pelvis. Alternatively, for the sensor positioned on the hand, the power spectrum of acceleration and angular velocity decreased in the movement frequency band. During the work task, following the performance of the fatiguing RPT, the power spectrum of acceleration and angular velocity increased in the movement frequency band for sensors positioned on the head, sternum, pelvis, and arm. Interestingly, for both the RPT and work task, Cohens’ d effect sizes were systematically larger for results extracted from angular velocity than acceleration. Although fatigue-related changes were task-specific between the RPT and the work task, fatigue systematically increased the power spectrum in the movement frequency band for the head, sternum, pelvis, which highlights the relevance of this indicator for assessing fatigue. Angular velocity may be more efficient to assess fatigue than acceleration. The use of low cost, wearable, and uncalibrated sensors, such as acceleration and gyroscope, in industrial settings is promising to assess muscle fatigue in workers assigned to upper limb repetitive tasks. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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21 pages, 1939 KiB  
Article
Significant Features for Human Activity Recognition Using Tri-Axial Accelerometers
by Mohamed Bennasar, Blaine A. Price, Daniel Gooch, Arosha K. Bandara and Bashar Nuseibeh
Sensors 2022, 22(19), 7482; https://doi.org/10.3390/s22197482 - 02 Oct 2022
Cited by 5 | Viewed by 2201
Abstract
Activity recognition using wearable sensors has become essential for a variety of applications. Tri-axial accelerometers are the most widely used sensor for activity recognition. Although various features have been used to capture patterns and classify the accelerometer signals to recognise activities, there is [...] Read more.
Activity recognition using wearable sensors has become essential for a variety of applications. Tri-axial accelerometers are the most widely used sensor for activity recognition. Although various features have been used to capture patterns and classify the accelerometer signals to recognise activities, there is no consensus on the best features to choose. Reducing the number of features can reduce the computational cost and complexity and enhance the performance of the classifiers. This paper identifies the signal features that have significant discriminative power between different human activities. It also investigates the effect of sensor placement location, the sampling frequency, and activity complexity on the selected features. A comprehensive list of 193 signal features has been extracted from accelerometer signals of four publicly available datasets, including features that have never been used before for activity recognition. Feature significance was measured using the Joint Mutual Information Maximisation (JMIM) method. Common significant features among all the datasets were identified. The results show that the sensor placement location does not significantly affect recognition performance, nor does it affect the significant sub-set of features. The results also showed that with high sampling frequency, features related to signal repeatability and regularity show high discriminative power. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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16 pages, 2645 KiB  
Article
Classification of Wheelchair Related Shoulder Loading Activities from Wearable Sensor Data: A Machine Learning Approach
by Wiebe H. K. de Vries, Sabrina Amrein, Ursina Arnet, Laura Mayrhuber, Cristina Ehrmann and H. E. J. Veeger
Sensors 2022, 22(19), 7404; https://doi.org/10.3390/s22197404 - 29 Sep 2022
Cited by 2 | Viewed by 1730
Abstract
Shoulder problems (pain and pathology) are highly prevalent in manual wheelchair users with spinal cord injury. These problems lead to limitations in activities of daily life (ADL), labor- and leisure participation, and increase the health care costs. Shoulder problems are often associated with [...] Read more.
Shoulder problems (pain and pathology) are highly prevalent in manual wheelchair users with spinal cord injury. These problems lead to limitations in activities of daily life (ADL), labor- and leisure participation, and increase the health care costs. Shoulder problems are often associated with the long-term reliance on the upper limbs, and the accompanying “shoulder load”. To make an estimation of daily shoulder load, it is crucial to know which ADL are performed and how these are executed in the free-living environment (in terms of magnitude, frequency, and duration). The aim of this study was to develop and validate methodology for the classification of wheelchair related shoulder loading ADL (SL-ADL) from wearable sensor data. Ten able bodied participants equipped with five Shimmer sensors on a wheelchair and upper extremity performed eight relevant SL-ADL. Deep learning networks using bidirectional long short-term memory networks were trained on sensor data (acceleration, gyroscope signals and EMG), using video annotated activities as the target. Overall, the trained algorithm performed well, with an accuracy of 98% and specificity of 99%. When reducing the input for training the network to data from only one sensor, the overall performance decreased to around 80% for all performance measures. The use of only forearm sensor data led to a better performance than the use of the upper arm sensor data. It can be concluded that a generalizable algorithm could be trained by a deep learning network to classify wheelchair related SL-ADL from the wearable sensor data. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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9 pages, 2272 KiB  
Article
To Live Together Is to Move Together: Social Actigraphy Applied to Healthy Elderly People
by Marco Rabuffetti, Ennio De Giovannini and Maurizio Ferrarin
Sensors 2022, 22(16), 6011; https://doi.org/10.3390/s22166011 - 11 Aug 2022
Cited by 1 | Viewed by 1038
Abstract
(1) Background: Actigraphic methods allow prolonged monitoring of human physical activity (PA) by wearable sensors in a real-life unsupervised context. They generally do not characterize the social context, and nearby persons can have a modulating effect on the performed PA. The present study [...] Read more.
(1) Background: Actigraphic methods allow prolonged monitoring of human physical activity (PA) by wearable sensors in a real-life unsupervised context. They generally do not characterize the social context, and nearby persons can have a modulating effect on the performed PA. The present study aims to apply an existing method for bimanual actigraphy to both components of a marital dyad to verify the level of association between the two PA profiles. Other dyad comparisons complete the overall figure. (2) Methods: Seven-day actigraphic recordings collected from both components of 20 married couples of retired, cohabiting, healthy subjects (age ranging from 58 to 87 years) were considered. (3) Results: PA profiles of a marital dyad are significantly more correlated (coefficient: 0.444) than unrelated couples (0.278). Interestingly, participants’ profiles compared with their own recording shifted by 24 h, evidencing an intermediate level of association (0.335). Data from the literature, the high association (0.875) of individual right and left wrist profiles, enforce the analysis. (4) Conclusions: The proposed method, called “social actigraphy”, confirmed that the partner has a relevant effect on one’s PA profile, thus suggesting involving the partner in programs concerning lifestyle changes and patient rehabilitation. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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17 pages, 5288 KiB  
Article
Smart Brace for Static and Dynamic Knee Laxity Measurement
by Paolo Bellitti, Michela Borghetti, Nicola Francesco Lopomo, Emilio Sardini and Mauro Serpelloni
Sensors 2022, 22(15), 5815; https://doi.org/10.3390/s22155815 - 04 Aug 2022
Cited by 4 | Viewed by 2608
Abstract
Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia [...] Read more.
Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia and femur under mechanical stress (i.e., laxity). Ligament laxity measurement is clinically valuable for diagnosing ACL injury and comparing possible outcomes of surgical procedures. In general, knee laxity assessment is manually performed and provides information to clinicians which is mainly subjective. Only recently quantitative assessment of knee laxity through instrumental approaches has been introduced and become a fundamental asset in clinical practice. However, the current solutions provide only partial information about either static or dynamic laxity. To support a multiparametric approach using a single device, an innovative smart knee brace for knee laxity evaluation was developed. Equipped with stretchable strain sensors and inertial measurement units (IMUs), the wearable system was designed to provide quantitative information concerning the drawer, Lachman, and pivot shift tests. We specifically characterized IMUs by using a reference sensor. Applying the Bland–Altman method, the limit of agreement was found to be less than 0.06 m/s2 for the accelerometer, 0.06 rad/s for the gyroscope and 0.08 μT for the magnetometer. By using an appropriate characterizing setup, the average gauge factor of the three strain sensors was 2.169. Finally, we realized a pilot study to compare the outcomes with a marker-based optoelectronic stereophotogrammetric system to verify the validity of the designed system. The preliminary findings for the capability of the system to discriminate possible ACL lesions are encouraging; in fact, the smart brace could be an effective support for an objective and quantitative diagnosis of ACL tear by supporting the simultaneous assessment of both rotational and translational laxity. To obtain reliable information about the real effectiveness of the system, further clinical validation is necessary. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 5382 KiB  
Article
Adjustments in Shoulder and Back Kinematics during Repetitive Palletizing Tasks
by Saeb R. Lamooki, Lora A. Cavuoto and Jiyeon Kang
Sensors 2022, 22(15), 5655; https://doi.org/10.3390/s22155655 - 28 Jul 2022
Cited by 3 | Viewed by 1505
Abstract
Repetitive task performance is a leading cause of musculoskeletal injuries among order-picking workers in warehouses. The repetition of lifting tasks increases the risk of back and shoulder injuries among these workers. While lifting in this industry is composed of loaded and unloaded picking [...] Read more.
Repetitive task performance is a leading cause of musculoskeletal injuries among order-picking workers in warehouses. The repetition of lifting tasks increases the risk of back and shoulder injuries among these workers. While lifting in this industry is composed of loaded and unloaded picking and placing, the existing literature does not address the separate analysis of the biomechanics of the back and shoulder for these events. To that end, we investigated the kinematics of the back and shoulder movements of nine healthy male participants who performed three sessions of a simulated de/palletization task. Their back and shoulder kinematics were sensed using an optical motion capture system to determine the back inclination and shoulder flexion. Comparison of the kinematics between the first and last sessions indicated statistically significant changes in the timings, angles, coordination between the back and shoulder, and moments around the shoulder (p<0.05). The majority of the significant changes were observed during the loaded events, which confirms the importance of the separation of these events for biomechanical analysis. This finding suggests that focusing worker evaluation on the loaded periods can provide important information to detect kinematic changes that may affect musculoskeletal injury risk. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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15 pages, 2778 KiB  
Article
Rendering Immersive Haptic Force Feedback via Neuromuscular Electrical Stimulation
by Elisa Galofaro, Erika D’Antonio, Nicola Lotti and Lorenzo Masia
Sensors 2022, 22(14), 5069; https://doi.org/10.3390/s22145069 - 06 Jul 2022
Cited by 10 | Viewed by 2734
Abstract
Haptic feedback is the sensory modality to enhance the so-called “immersion”, meant as the extent to which senses are engaged by the mediated environment during virtual reality applications. However, it can be challenging to meet this requirement using conventional robotic design approaches that [...] Read more.
Haptic feedback is the sensory modality to enhance the so-called “immersion”, meant as the extent to which senses are engaged by the mediated environment during virtual reality applications. However, it can be challenging to meet this requirement using conventional robotic design approaches that rely on rigid mechanical systems with limited workspace and bandwidth. An alternative solution can be seen in the adoption of lightweight wearable systems equipped with Neuromuscular Electrical Stimulation (NMES): in fact, NMES offers a wide range of different forces and qualities of haptic feedback. In this study, we present an experimental setup able to enrich the virtual reality experience by employing NMES to create in the antagonists’ muscles the haptic sensation of being loaded. We developed a subject-specific biomechanical model that estimated elbow torque during object lifting to deliver suitable electrical muscle stimulations. We experimentally tested our system by exploring the differences between the implemented NMES-based haptic feedback (NMES condition), a physical lifted object (Physical condition), and a condition without haptic feedback (Visual condition) in terms of kinematic response, metabolic effort, and participants’ perception of fatigue. Our results showed that both in terms of metabolic consumption and user fatigue perception, the condition with electrical stimulation and the condition with the real weight differed significantly from the condition without any load: the implemented feedback was able to faithfully reproduce interactions with objects, suggesting its possible application in different areas such as gaming, work risk assessment simulation, and education. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 1700 KiB  
Article
External Load of Flamenco Zap-3 Footwork Test: Use of PlayerLoad Concept with Triaxial Accelerometry
by Ningyi Zhang, Sebastián Gómez-Lozano, Ross Armstrong, Hui Liu and Alfonso Vargas-Macías
Sensors 2022, 22(13), 4847; https://doi.org/10.3390/s22134847 - 27 Jun 2022
Cited by 1 | Viewed by 1874
Abstract
The intense footwork required in flamenco dance may result in pain and injury. This study aimed to quantify the external load of the flamenco Zapateado-3 (Zap-3) footwork via triaxial accelerometry in the form of PlayerLoad (PL), comparing the difference in external loads at [...] Read more.
The intense footwork required in flamenco dance may result in pain and injury. This study aimed to quantify the external load of the flamenco Zapateado-3 (Zap-3) footwork via triaxial accelerometry in the form of PlayerLoad (PL), comparing the difference in external loads at the fifth lumbar vertebra (L5), the seventh cervical vertebra (C7) and the dominant ankle (DA), and to explore whether the speed, position, axis and proficiency level of the flamenco dancer affected the external load. Twelve flamenco dancers, divided into professional and amateur groups, completed a 15-s Zap-3 footwork routine at different speeds. Triaxial accelerometry sensors were positioned at the DA, L5 and C7 and were utilized to calculate the total PlayerLoad (PLTOTAL), uniaxial PlayerLoad (PLUNI) and uniaxial contributions (PL%). For both PLTOTAL and PLUNI, this study identified significant effects of speed and position (p < 0.001), as well as the interaction between speed and position (p ≤ 0.001), and at the DA, values were significantly higher (p < 0.001) than those at C7 and L5. Significant single axis and group effects (p < 0.001) and effects of the interactions between the position and a single axis and the group and speed (p ≤ 0.001) were also identified for PLUNI. Medial-lateral PL% represented a larger contribution compared with anterior-posterior PL% and vertical PL% (p < 0.001). A significant interaction effect of position and PL% (p < 0.001) also existed. In conclusion, the Zap-3 footwork produced a significant external load at different positions, and it was affected by speed, axis and the proficiency level of the flamenco dancer. Although the ankle bears the most external load when dancing the flamenco, some external load caused by significant vibrations is also borne by the lumbar and cervical vertebrae. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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14 pages, 1341 KiB  
Article
Events Detection of Anticipatory Postural Adjustments through a Wearable Accelerometer Sensor Is Comparable to That Measured by the Force Platform in Subjects with Parkinson’s Disease
by Tiziana Lencioni, Mario Meloni, Thomas Bowman, Alberto Marzegan, Antonio Caronni, Ilaria Carpinella, Anna Castagna, Valerio Gower, Maurizio Ferrarin and Elisa Pelosin
Sensors 2022, 22(7), 2668; https://doi.org/10.3390/s22072668 - 30 Mar 2022
Cited by 4 | Viewed by 2817
Abstract
Out-of-the-lab instrumented gait testing focuses on steady-state gait and usually does not include gait initiation (GI) measures. GI involves Anticipatory Postural Adjustments (APAs), which propel the center of mass (COM) forward and laterally before the first step. These movements are impaired in persons [...] Read more.
Out-of-the-lab instrumented gait testing focuses on steady-state gait and usually does not include gait initiation (GI) measures. GI involves Anticipatory Postural Adjustments (APAs), which propel the center of mass (COM) forward and laterally before the first step. These movements are impaired in persons with Parkinson’s disease (PD), contributing to their pathological gait. The use of a simple GI testing system, outside the lab, would allow improving gait rehabilitation of PD patients. Here, we evaluated the metrological quality of using a single inertial measurement unit for APA detection as compared with the use of a gold-standard system, i.e., the force platforms. Twenty-five PD and eight elderly subjects (ELD) were asked to initiate gait in response to auditory stimuli while wearing an IMU on the trunk. Temporal parameters (APA-Onset, Time-to-Toe-Off, Time-to-Heel-Strike, APA-Duration, Swing-Duration) extracted from the accelerometric data and force platforms were significantly correlated (mean(SD), r: 0.99(0.01), slope: 0.97(0.02)) showing a good level of agreement (LOA [s]: 0.04(0.01), CV [%]: 2.9(1.7)). PD showed longer APA-Duration compared to ELD ([s] 0.81(0.17) vs. 0.59(0.09) p < 0.01). APA parameters showed moderate correlation with the MDS-UPDRS Rigidity, Characterizing-FOG questionnaire and FAB-2 planning. The single IMU-based reconstruction algorithm was effective in measuring APAs timings in PD. The current work sets the stage for future developments of tele-rehabilitation and home-based exercises. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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10 pages, 729 KiB  
Communication
Gait Parameters in Healthy Preschool and School Children Assessed Using Wireless Inertial Sensor
by Ewa Gieysztor, Mateusz Kowal and Małgorzata Paprocka-Borowicz
Sensors 2021, 21(19), 6423; https://doi.org/10.3390/s21196423 - 26 Sep 2021
Cited by 10 | Viewed by 1874
Abstract
Background: The objective gait assessment in children has become more popular. Basis parameters for comparison during the examination are advisable. Objectives: The study aim was to investigate the typical gait parameters of healthy preschool and school children, using a wireless inertial sensor as [...] Read more.
Background: The objective gait assessment in children has become more popular. Basis parameters for comparison during the examination are advisable. Objectives: The study aim was to investigate the typical gait parameters of healthy preschool and school children, using a wireless inertial sensor as the reference for atypical gait. The additional aim was to compare the specific gait parameters in the younger and older group of children. Methods: One hundred and sixty-one children’s gait parameters were evaluated by a G-Walk BTS G-SENSOR smart analyzer. The children were walking barefoot, at a self-selected speed, on a five-meter walkway, and they turned around and go back twice. Results: Age significantly influences most of the spatiotemporal parameters. The support phase becomes shorter with age. Accordingly, the swing phase becomes longer with age. The results also show that older children need shorter double support and have longer single support. Moreover, the pelvic tilt symmetry index is higher with increasing age. In each age division, the smallest variation in all gait parameters within the oldest group of examined children was observed. A comparison between the left and right side gait parameters shows the higher difference in boys than in girls. A significant difference was calculated in the pelvic obliquity symmetry index. Girls had significantly more symmetrical obliquity than boys. Conclusions: the research indicates the basic parameters of typical children’s gait, which may be a reference to atypical gait in the case of trauma or disability. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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18 pages, 5656 KiB  
Article
Lower Back Injury Prevention and Sensitization of Hip Hinge with Neutral Spine Using Wearable Sensors during Lifting Exercises
by Florian Michaud, Manuel Pérez Soto, Urbano Lugrís and Javier Cuadrado
Sensors 2021, 21(16), 5487; https://doi.org/10.3390/s21165487 - 14 Aug 2021
Cited by 7 | Viewed by 7828
Abstract
The popularization and industrialization of fitness over the past decade, with the rise of big box gyms and group classes, has reduced the quality of the basic formation and assessment of practitioners, which has increased the risk of injury. For most lifting exercises, [...] Read more.
The popularization and industrialization of fitness over the past decade, with the rise of big box gyms and group classes, has reduced the quality of the basic formation and assessment of practitioners, which has increased the risk of injury. For most lifting exercises, a universal recommendation is maintaining a neutral spine position. Otherwise, there is a risk of muscle injury or, even worse, of a herniated disc. Maintaining the spine in a neutral position during lifting exercises is difficult, as it requires good core stability, a good hip hinge and, above all, observation of the posture in order to keep it correct. For this reason, in this work the authors propose the prevention of lumbar injuries with two inertial measurement units. The relative rotation between two sensors was measured for 39 voluntary subjects during the performance of two lifting exercises: the American kettlebell swing and the deadlift. The accuracy of the measurements was evaluated, especially in the presence of metals and for fast movements, by comparing the obtained results with those from an optical motion capture system. Finally, in order to develop a tool for improving sport performance and preventing injury, the authors analyzed the recorded motions, seeking to identify the most relevant parameters for good and safe lifting execution. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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15 pages, 538 KiB  
Article
Reliability and Validity of the Polhemus Liberty System for Upper Body Segment and Joint Angular Kinematics of Elite Golfers
by Matilda Jane Wheare, Maximillian J. Nelson, Ryan Lumsden, Alec Buttfield and Robert George Crowther
Sensors 2021, 21(13), 4330; https://doi.org/10.3390/s21134330 - 24 Jun 2021
Cited by 6 | Viewed by 2261
Abstract
Golf swing analysis is common in both recreational and professional levels where players are searching for improvements in shot accuracy and distance. The use of motion analysis systems such as the portable Polhemus Liberty system is gaining interest by coaches and players; however, [...] Read more.
Golf swing analysis is common in both recreational and professional levels where players are searching for improvements in shot accuracy and distance. The use of motion analysis systems such as the portable Polhemus Liberty system is gaining interest by coaches and players; however, to date, no research has examined the usefulness of the Polhemus Liberty system for golf swing analysis. Therefore, the purpose of this study was to determine the reliability of the Polhemus Liberty system and validity compared to the VICON Nexus motion analysis system when assessing segment (pelvis and thorax) and joint (shoulder, elbow and wrist) angular kinematics during a golf swing at key events (address, top of backswing and impact). Fifteen elite amateur/professional golfers performed ten golf swing trials within specified bounds using their 5-iron club. Reliability was assessed using interclass coefficient, effect size and t-test statistics by all participants completing two separate testing sessions on separate days following the same experimental protocol. Validity was assessed using effect size, Pearson correlation and t-test statistics by comparing swings captured using both Polhemus Liberty and VICON Nexus concurrently. Results demonstrated no difference in ball outcome results using the Trackman launch monitor (P > 0.05) and that the Polhemus Liberty system was reliable across the two sessions for all segment (pelvis and thorax) and joint (lead shoulder (gleno-humeral joint), elbow and wrist) angular kinematics (P > 0.05). Validity analysis showed that the Polhemus Liberty system for the segments (pelvis and thorax) and joints (lead shoulder and wrist) were different compared to the VICON Nexus data at key events during the golf swing. Although validity could not be confirmed against VICON Nexus modeling, the Polhemus Liberty system may still be useful for golf swing analysis across training sessions. However, caution should be applied when comparing data from the system to published research data using different motion analysis methods. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 1248 KiB  
Article
Validation of Plantar Pressure and Reaction Force Measured by Moticon Pressure Sensor Insoles on a Concept2 Rowing Ergometer
by Georgina Kate Barratt, Clint Bellenger, Eileen Yule Robertson, Jason Lane and Robert George Crowther
Sensors 2021, 21(7), 2418; https://doi.org/10.3390/s21072418 - 01 Apr 2021
Cited by 12 | Viewed by 3362
Abstract
The purpose of this study was to determine the reliability and validity of plantar pressure and reaction force measured using the Moticon and Pedar-x sensor insoles while rowing on a Concept2 ergometer. Nineteen participants performed four 500 m trials of ergometer rowing at [...] Read more.
The purpose of this study was to determine the reliability and validity of plantar pressure and reaction force measured using the Moticon and Pedar-x sensor insoles while rowing on a Concept2 ergometer. Nineteen participants performed four 500 m trials of ergometer rowing at 22–24 strokes/min; two trials wearing Moticon insoles and two wearing Pedar-x insoles in a randomised order. Moticon and Pedar-x insoles both showed moderate to strong test–retest reliability (ICC = 0.57–0.92) for mean and peak plantar pressure and reaction force. Paired t-test demonstrated a significant difference (p < 0.001) between Moticon and Pedar-x insoles, effect size showed a large bias (ES > 1.13), and Pearson’s correlation (r < 0.37) showed poor agreement for all plantar pressure and reaction force variables. Compared to Pedar-x, the Moticon insoles demonstrated poor validity, however, the Moticon insoles had strong reliability. Due to poor validity, caution should be used when considering Moticon insoles to assess changes in pressure and force reliably over time, across multiple trials or sessions. Moticon’s wireless and user-friendly application would be beneficial for assessing and monitoring biomechanical parameters in rowing if validity between measures of interest and Moticon’s results can be established. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 15861 KiB  
Article
Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses—A Machine Learning Approach
by Hamed Darbandi, Filipe Serra Bragança, Berend Jan van der Zwaag, John Voskamp, Annik Imogen Gmel, Eyrún Halla Haraldsdóttir and Paul Havinga
Sensors 2021, 21(3), 798; https://doi.org/10.3390/s21030798 - 26 Jan 2021
Cited by 14 | Viewed by 4800
Abstract
Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU [...] Read more.
Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU signals integration. In an attempt to overcome these issues, we have investigated the possibility of estimating the horse speed by developing machine learning (ML) models using the signals from seven body-mounted IMUs. Since motion patterns extracted from IMU signals are different between breeds and gaits, we trained the models based on data from 40 Icelandic and Franches-Montagnes horses during walk, trot, tölt, pace, and canter. In addition, we studied the estimation accuracy between IMU locations on the body (sacrum, withers, head, and limbs). The models were evaluated per gait and were compared between ML algorithms and IMU location. The model yielded the highest estimation accuracy of speed (RMSE = 0.25 m/s) within equine and most of human speed estimation literature. In conclusion, highly accurate horse speed estimation models, independent of IMU(s) location on-body and gait, were developed using ML. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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12 pages, 5414 KiB  
Article
Muscle Co-Activation around the Knee during Different Walking Speeds in Healthy Females
by Abdel-Rahman Akl, Pedro Gonçalves, Pedro Fonseca, Amr Hassan, João Paulo Vilas-Boas and Filipe Conceição
Sensors 2021, 21(3), 677; https://doi.org/10.3390/s21030677 - 20 Jan 2021
Cited by 6 | Viewed by 2886
Abstract
The purpose of this study was to examine the changes in co-activation around the knee joint during different walking speeds in healthy females using the co-activation index. Ten healthy females (age: 21.20 ± 7.21 years, height: 164.00 ± 4.00 cm, mass: 60.60 ± [...] Read more.
The purpose of this study was to examine the changes in co-activation around the knee joint during different walking speeds in healthy females using the co-activation index. Ten healthy females (age: 21.20 ± 7.21 years, height: 164.00 ± 4.00 cm, mass: 60.60 ± 4.99 kg) participated in this study and performed three walking speeds (slow, normal, and fast). A Qualisys 11-camera motion analysis system sampling at a frequency of 200 Hz was synchronized with a Trigno EMG Wireless system operating at a 2000 Hz sampling frequency. A significant decrease in the co-activation index of thigh muscles was observed between the slow and fast, and between the normal and fast, walking speeds during all walking phases. A non-significant difference was observed between the slow and normal walking speeds during most walking phases, except the second double support phase, during which the difference was significant. A negative relationship was found between walking speed and the co-activation index of thigh muscles in all speeds during walking phases: first double support (r = −0.3386, p < 0.001), single support (r = −0.2144, p < 0.01), second double support (r = −0.4949, p < 0.001), and Swing (r = −0.1639, p < 0.05). In conclusion, the results indicated high variability of thigh muscle co-activation in healthy females during the different walking speeds, and a decrease in the co-activation of the thigh muscles with the increase of speed. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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20 pages, 3280 KiB  
Article
Equimetrix Device: Criteria Based Validation and Reliability Analysis of the Center of Mass and Base of Support of a Human Postural Assessment System
by Pedro Fonseca, Manoela Sousa, Ricardo Sebastião, Márcio Goethel, Pierre Barralon, Igone Idigoras, Filipa Sousa, Leandro Machado and João Paulo Vilas-Boas
Sensors 2021, 21(2), 374; https://doi.org/10.3390/s21020374 - 07 Jan 2021
Cited by 1 | Viewed by 2948
Abstract
Human postural control is a fundamental ability for static and dynamic tasks, especially in hiper- and hipo-functional populations, such as the elderly. The Equimetrix is a clinical device developed to assess both the base of support (BoS) and the center of mass (CoM) [...] Read more.
Human postural control is a fundamental ability for static and dynamic tasks, especially in hiper- and hipo-functional populations, such as the elderly. The Equimetrix is a clinical device developed to assess both the base of support (BoS) and the center of mass (CoM) dynamics, thus allowing their use as new evaluation and training tools. This study aims to perform a criteria based validation of Equimetrix by comparing the BoS and CoM data with gold-standard equipment. A motion capture system, force platform, and pressure mat were used to calculate the CoM, center of pressure (CoP) and BoS during bipedal, unipedal, feet together and full tandem stances. Results demonstrate an excellent reliability of Equimetrix in terms of spatial accuracy of the CoM, although over-estimating the CoM height. Differences were found when comparing Mean velocity Path with the CoM, but not with the CoP, indicating a lower reliability in time-based parameters. The Equimetrix presents a tendency to overestimate the BoS, with mixed reliability values, which may be related to the different size of sensing elements between the Equimetrix and the pressure sensing mat. These are encouraging results that should be further explored during dynamic tasks. Full article
(This article belongs to the Special Issue Wearable Sensors for Biomechanics Applications)
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