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Wearable or Markerless Sensors for Gait and Movement Analysis
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Wearable or Markerless Sensors for Gait and Movement Analysis

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

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 34706

Special Issue Editors

Dr. Helena Grip

E-Mail Website
Guest Editor
Department of Radiation Sciences, Biomedical Engineering, Umeå University, 901 87 Umeå, Sweden
Interests: medical technology; biomedical engineering; movement analysis; motor control
Dr. Fredrik Öhberg

E-Mail Website
Guest Editor
Department of Radiation Science, Umeå University, 901 87 Umeå, Sweden
Interests: medical technology; biomedical engineering; movement analysis; artificial intelligence

Special Issue Information

Dear Colleagues,

Innovative solutions based on wearable sensors or markerless sensing for capturing human motion have emerged in the market and enabled applications for motion analysis outside the classical movement laboratories. Applications are, for example, physical activity monitoring, medical research and clinical applications such as clinical gait analysis and fall detection, ergonomic and sports applications, animations of human movement, video games, to name a few.

This Special Issue addresses innovative developments, technologies, and challenges related to wearable and markerless motion sensing and seeks the latest findings from ongoing research. Review articles and meta-analyses that provide readers with current research trends and solutions are also welcome. Potential topics include, but are not limited to, the following:

  • New algorithms and methods for motion capture and motion analysis;
  • Innovative wearable sensor or markerless systems for human motion capture;
  • Novel algorithms for motion pattern recognition (for example, using artificial neural networks);
  • New sensor applications within the field of medicine, sports and ergonomics;
  • Biomechanical modeling (joint kinetics and kinematics);
  • Sensor applications for prosthetics and orthotics.

Dr. Helena Grip
Dr. Fredrik Öhberg
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. Sensors 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 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.

Published Papers (17 papers)

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Research

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14 pages, 4147 KiB  
Article
A Method for Quantifying Back Flexion/Extension from Three Inertial Measurement Units Mounted on a Horse’s Withers, Thoracolumbar Region, and Pelvis
by Chloé Hatrisse, Claire Macaire, Camille Hebert, Sandrine Hanne-Poujade, Emeline De Azevedo, Fabrice Audigié, Khalil Ben Mansour, Frederic Marin, Pauline Martin, Neila Mezghani, Henry Chateau and Laurence Chèze
Sensors 2023, 23(24), 9625; https://doi.org/10.3390/s23249625 - 5 Dec 2023
Viewed by 1719
Abstract
Back mobility is a criterion of well-being in a horse. Veterinarians visually assess the mobility of a horse’s back during a locomotor examination. Quantifying it with on-board technology could be a major breakthrough to help them. The aim of this study was to [...] Read more.
Back mobility is a criterion of well-being in a horse. Veterinarians visually assess the mobility of a horse’s back during a locomotor examination. Quantifying it with on-board technology could be a major breakthrough to help them. The aim of this study was to evaluate the accuracy of a method of quantifying the back mobility of horses from inertial measurement units (IMUs) compared to motion capture (MOCAP) as a gold standard. Reflective markers and IMUs were positioned on the withers, eighteenth thoracic vertebra, and pelvis of four sound horses. The horses performed a walk and trot in straight lines and performed a gallop in circles on a soft surface. The developed method, based on the three IMUs, consists of calculating the flexion/extension angle of the thoracolumbar region. The IMU method showed a mean bias of 0.8° (±1.5°) (mean (±SD)) and 0.8° (±1.4°), respectively, for the flexion and extension movements, all gaits combined, compared to the MOCAP method. The results of this study suggest that the developed method has a similar accuracy to that of MOCAP, opening up possibilities for easy measurements under field conditions. Future studies will need to examine the correlations between these biomechanical measures and clinicians’ visual assessment of back mobility defects. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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23 pages, 7615 KiB  
Article
Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?
by Wenyi Lin, Fikret Isik Karahanoglu, Dimitrios Psaltos, Lukas Adamowicz, Mar Santamaria, Xuemei Cai, Charmaine Demanuele and Junrui Di
Sensors 2023, 23(20), 8542; https://doi.org/10.3390/s23208542 - 18 Oct 2023
Cited by 1 | Viewed by 1563
Abstract
Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed [...] Read more.
Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients’ comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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16 pages, 1223 KiB  
Article
The Use of Embedded IMU Insoles to Assess Gait Parameters: A Validation and Test-Retest Reliability Study
by Louis Riglet, Fabien Nicol, Audrey Leonard, Nicolas Eby, Lauranne Claquesin, Baptiste Orliac, Paul Ornetti, Davy Laroche and Mathieu Gueugnon
Sensors 2023, 23(19), 8155; https://doi.org/10.3390/s23198155 - 28 Sep 2023
Cited by 1 | Viewed by 1161
Abstract
Wireless wearable insoles are interesting tools to collect gait parameters during daily life activities. However, studies have to be performed specifically for each type of insoles on a big data set to validate the measurement in ecological situations. This study aims to assess [...] Read more.
Wireless wearable insoles are interesting tools to collect gait parameters during daily life activities. However, studies have to be performed specifically for each type of insoles on a big data set to validate the measurement in ecological situations. This study aims to assess the criterion validity and test-retest reliability of gait parameters from wearable insoles compared to motion capture system. Gait of 30 healthy participants was recorded using DSPro® insoles and a motion capture system during overground and treadmill walking at three different speeds. Criterion validity and test-retest reliability of spatio-temporal parameters were estimated with an intraclass correlation coefficient (ICC). For both systems, reliability was found higher than 0.70 for all variables (p < 0.001) except for minimum toe clearance (ICC < 0.50) with motion capture system during overground walking. Regardless of speed and condition of walking, Speed, Cadence, Stride Length, Stride Time and Stance Time variables were validated (ICC > 0.90; p < 0.001). During walking on treadmill, loading time was not validated during slow speed (ICC < 0.70). This study highlights good criterion validity and test-retest reliability of spatiotemporal gait parameters measurement using wearable insoles and opens a new possibility to improve care management of patients using clinical gait analysis in daily life activities. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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24 pages, 2974 KiB  
Article
Drift-Free Joint Angle Calculation Using Inertial Measurement Units without Magnetometers: An Exploration of Sensor Fusion Methods for the Elbow and Wrist
by Howard Chen, Mark C. Schall, Jr., Scott M. Martin and Nathan B. Fethke
Sensors 2023, 23(16), 7053; https://doi.org/10.3390/s23167053 - 9 Aug 2023
Cited by 1 | Viewed by 1616
Abstract
Joint angles of the lower extremities have been calculated using gyroscope and accelerometer measurements from inertial measurement units (IMUs) without sensor drift by leveraging kinematic constraints. However, it is unknown whether these methods are generalizable to the upper extremity due to differences in [...] Read more.
Joint angles of the lower extremities have been calculated using gyroscope and accelerometer measurements from inertial measurement units (IMUs) without sensor drift by leveraging kinematic constraints. However, it is unknown whether these methods are generalizable to the upper extremity due to differences in motion dynamics. Furthermore, the extent that post-processed sensor fusion algorithms can improve measurement accuracy relative to more commonly used Kalman filter-based methods remains unknown. This study calculated the elbow and wrist joint angles of 13 participants performing a simple ≥30 min material transfer task at three rates (slow, medium, fast) using IMUs and kinematic constraints. The best-performing sensor fusion algorithm produced total root mean square errors (i.e., encompassing all three motion planes) of 6.6°, 3.6°, and 2.0° for the slow, medium, and fast transfer rates for the elbow and 2.2°, 1.7°, and 1.5° for the wrist, respectively. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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13 pages, 432 KiB  
Article
Raw Acceleration from Wrist- and Hip-Worn Accelerometers Corresponds with Mechanical Loading in Children and Adolescents
by Gemma Brailey, Brad Metcalf, Lisa Price, Sean Cumming and Victoria Stiles
Sensors 2023, 23(15), 6943; https://doi.org/10.3390/s23156943 - 4 Aug 2023
Cited by 2 | Viewed by 941
Abstract
The purpose of this study was to investigate associations between peak magnitudes of raw acceleration (g) from wrist- and hip-worn accelerometers and ground reaction force (GRF) variables in a large sample of children and adolescents. A total of 269 participants (127 boys, 142 [...] Read more.
The purpose of this study was to investigate associations between peak magnitudes of raw acceleration (g) from wrist- and hip-worn accelerometers and ground reaction force (GRF) variables in a large sample of children and adolescents. A total of 269 participants (127 boys, 142 girls; age: 12.3 ± 2.0 yr) performed walking, running, jumping (<5 cm; >5 cm) and single-leg hopping on a force plate. A GENEActiv accelerometer was worn on the left wrist, and an Actigraph GT3X+ was worn on the right wrist and hip throughout. Mixed-effects linear regression was used to assess the relationships between peak magnitudes of raw acceleration and loading. Raw acceleration from both wrist and hip-worn accelerometers was strongly and significantly associated with loading (all p’s < 0.05). Body mass and maturity status (pre/post-PHV) were also significantly associated with loading, whereas age, sex and height were not identified as significant predictors. The final models for the GENEActiv wrist, Actigraph wrist and Actigraph hip explained 81.1%, 81.9% and 79.9% of the variation in loading, respectively. This study demonstrates that wrist- and hip-worn accelerometers that output raw acceleration are appropriate for use to monitor the loading exerted on the skeleton and are able to detect short bursts of high-intensity activity that are pertinent to bone health. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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19 pages, 4860 KiB  
Article
Automated Gait Analysis Based on a Marker-Free Pose Estimation Model
by Chang Soon Tony Hii, Kok Beng Gan, Nasharuddin Zainal, Norlinah Mohamed Ibrahim, Shahrul Azmin, Siti Hajar Mat Desa, Bart van de Warrenburg and Huay Woon You
Sensors 2023, 23(14), 6489; https://doi.org/10.3390/s23146489 - 18 Jul 2023
Cited by 5 | Viewed by 2576
Abstract
Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, [...] Read more.
Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, and requires specialized equipment and trained personnel. Markerless gait analysis using 2D pose estimation techniques has emerged as a potential solution, but it still requires significant computational resources and human involvement, making it challenging to use. This research proposes an automated method for temporal gait analysis that employs the MediaPipe Pose, a low-computational-resource pose estimation model. The study validated this approach against the Vicon motion capture system to evaluate its reliability. The findings reveal that this approach demonstrates good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all temporal gait parameters except for double support time (right leg switched to left leg) and swing time (right), which only exhibit a moderate (ICC(2,1) > 0.50) agreement. Additionally, this approach produces temporal gait parameters with low mean absolute error. It will be useful in monitoring changes in gait and evaluating the effectiveness of interventions such as rehabilitation or training programs in the community. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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11 pages, 1701 KiB  
Communication
Measurement of Trunk Movement during Sit-to-Stand Motion Using Laser Range Finders: A Preliminary Study
by Haruki Toda, Kiyohiro Omori, Katsuya Fukui and Takaaki Chin
Sensors 2023, 23(4), 2022; https://doi.org/10.3390/s23042022 - 10 Feb 2023
Viewed by 1497
Abstract
The sit-to-stand (STS) motion evaluates physical functions in frail older adults. Mounting sensors or using a camera is necessary to measure trunk movement during STS motion. Therefore, we developed a simple measurement method by embedding laser range finders in the backrests and seats [...] Read more.
The sit-to-stand (STS) motion evaluates physical functions in frail older adults. Mounting sensors or using a camera is necessary to measure trunk movement during STS motion. Therefore, we developed a simple measurement method by embedding laser range finders in the backrests and seats of chairs that can be used in daily life situations. The objective of this study was to validate the performance of the proposed measurement method in comparison with that of the optical motion capture (MoCap) system during STS motion. The STS motions of three healthy young adults were simultaneously measured under seven conditions using a chair with embedded sensors and the optical MoCap system. We evaluated the waveform similarity, absolute error, and relationship of the trunk joint angular excursions between these measurement methods. The experimental results indicated high waveform similarity in the trunk flexion phase regardless of STS conditions. Furthermore, a strong relationship was observed between the two measurement methods with respect to the angular excursion of the trunk flexion. Although the angular excursion of the trunk extension exhibited a large error, the developed chair with embedded sensors evaluated trunk flexion during the STS motion, which is a characteristic of frail older adults. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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16 pages, 3728 KiB  
Article
Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera
by Fraser Young, Rachel Mason, Rosie Morris, Samuel Stuart and Alan Godfrey
Sensors 2023, 23(2), 696; https://doi.org/10.3390/s23020696 - 7 Jan 2023
Cited by 4 | Viewed by 2617
Abstract
Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often [...] Read more.
Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google’s pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01–0.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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26 pages, 4743 KiB  
Article
Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System
by Daniele Borzelli, Stefano Pastorelli, Andrea d’Avella and Laura Gastaldi
Sensors 2023, 23(2), 673; https://doi.org/10.3390/s23020673 - 6 Jan 2023
Cited by 3 | Viewed by 1758
Abstract
In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider [...] Read more.
In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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17 pages, 3358 KiB  
Article
A Framework for Analytical Validation of Inertial-Sensor-Based Knee Kinematics Using a Six-Degrees-of-Freedom Joint Simulator
by Ariana Ortigas Vásquez, Allan Maas, Renate List, Pascal Schütz, William R. Taylor and Thomas M. Grupp
Sensors 2023, 23(1), 348; https://doi.org/10.3390/s23010348 - 29 Dec 2022
Cited by 3 | Viewed by 1856
Abstract
The success of kinematic analysis that relies on inertial measurement units (IMUs) heavily depends on the performance of the underlying algorithms. Quantifying the level of uncertainty associated with the models and approximations implemented within these algorithms, without the complication of soft-tissue artefact, is [...] Read more.
The success of kinematic analysis that relies on inertial measurement units (IMUs) heavily depends on the performance of the underlying algorithms. Quantifying the level of uncertainty associated with the models and approximations implemented within these algorithms, without the complication of soft-tissue artefact, is therefore critical. To this end, this study aimed to assess the rotational errors associated with controlled movements. Here, data of six total knee arthroplasty patients from a previously published fluoroscopy study were used to simulate realistic kinematics of daily activities using IMUs mounted to a six-degrees-of-freedom joint simulator. A model-based method involving extended Kalman filtering to derive rotational kinematics from inertial measurements was tested and compared against the ground truth simulator values. The algorithm demonstrated excellent accuracy (root-mean-square error ≤0.9°, maximum absolute error ≤3.2°) in estimating three-dimensional rotational knee kinematics during level walking. Although maximum absolute errors linked to stair descent and sit-to-stand-to-sit rose to 5.2° and 10.8°, respectively, root-mean-square errors peaked at 1.9° and 7.5°. This study hereby describes an accurate framework for evaluating the suitability of the underlying kinematic models and assumptions of an IMU-based motion analysis system, facilitating the future validation of analogous tools. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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16 pages, 3121 KiB  
Article
Validity and Reliability of Wearable Motion Sensors for Clinical Assessment of Shoulder Function in Brachial Plexus Birth Injury
by Helena Grip, Anna Källströmer and Fredrik Öhberg
Sensors 2022, 22(23), 9557; https://doi.org/10.3390/s22239557 - 6 Dec 2022
Cited by 2 | Viewed by 2069
Abstract
The modified Mallet scale (MMS) is commonly used to grade shoulder function in brachial plexus birth injury (BPBI) but has limited sensitivity and cannot grade scapulothoracic and glenohumeral mobility. This study aims to evaluate if the addition of a wearable inertial movement unit [...] Read more.
The modified Mallet scale (MMS) is commonly used to grade shoulder function in brachial plexus birth injury (BPBI) but has limited sensitivity and cannot grade scapulothoracic and glenohumeral mobility. This study aims to evaluate if the addition of a wearable inertial movement unit (IMU) system could improve clinical assessment based on MMS. The system validity was analyzed with simultaneous measurements with the IMU system and an optical camera system in three asymptomatic individuals. Test–retest and interrater reliability were analyzed in nine asymptomatic individuals and six BPBI patients. IMUs were placed on the upper arm, forearm, scapula, and thorax. Peak angles, range of motion, and average joint angular speed in the shoulder, scapulothoracic, glenohumeral, and elbow joints were analyzed during mobility assessments and MMS tasks. In the validity tests, clusters of reflective markers were placed on the sensors. The validity was high with an error standard deviation below 3.6°. Intraclass correlation coefficients showed that 90.3% of the 69 outcome scores showed good-to-excellent test–retest reliability, and 41% of the scores gave significant differences between BPBI patients and controls with good-to-excellent test–retest reliability. The interrater reliability was moderate to excellent, implying that standardization is important if the patient is followed-up longitudinally. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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8 pages, 826 KiB  
Article
A Pilot Study on the Inter-Operator Reproducibility of a Wireless Sensors-Based System for Quantifying Gait Asymmetries in Horses
by Iris Timmerman, Claire Macaire, Sandrine Hanne-Poujade, Lélia Bertoni, Pauline Martin, Frédéric Marin and Henry Chateau
Sensors 2022, 22(23), 9533; https://doi.org/10.3390/s22239533 - 6 Dec 2022
Cited by 2 | Viewed by 1695
Abstract
Repeatability and reproducibility of any measuring system must be evaluated to assess possible limitations for its use. The objective of this study was to establish the repeatability and the inter-operator reproducibility of a sensors-based system (EQUISYM®) for quantifying gait asymmetries in [...] Read more.
Repeatability and reproducibility of any measuring system must be evaluated to assess possible limitations for its use. The objective of this study was to establish the repeatability and the inter-operator reproducibility of a sensors-based system (EQUISYM®) for quantifying gait asymmetries in horses.. Seven wireless IMUs were placed on the head, the withers, the pelvis, and the 4 cannon bones on three horses, by four different operators, four times on each horse, which led to a total of 48 repetitions randomly assigned. Data were collected along three consecutive days and analysed to calculate total variance, standard deviation and the variance attributable to the operator on multiple asymmetry variables. Maximal percentage of variance due to the operator (calculated out of the total variance) was 5.3% and was related to the sensor placed on the head. The results suggest a good reproducibility of IMU-based gait analysis systems for different operators repositioning the system and repeating the same measurements at a succession of time intervals. Future studies will be useful to confirm that inter-operator reproducibility remains valid in larger groups and on horses with different degrees of locomotor asymmetry. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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32 pages, 7073 KiB  
Article
Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits
by Michael V. Potter, Stephen M. Cain, Lauro V. Ojeda, Reed D. Gurchiek, Ryan S. McGinnis and Noel C. Perkins
Sensors 2022, 22(21), 8398; https://doi.org/10.3390/s22218398 - 1 Nov 2022
Cited by 5 | Viewed by 2396
Abstract
Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, stride length, and step width using data from an [...] Read more.
Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, stride length, and step width using data from an array of seven body-worn IMUs. Importantly, this paper contributes a novel joint axis measurement correction that reduces joint angle drift errors without assumptions of strict hinge-like joint behaviors of the hip and knee. We evaluate the method compared to two optical motion capture methods on twenty human subjects performing six different types of walking gait consisting of forward walking (at three speeds), backward walking, and lateral walking (left and right). For all gaits, RMS differences in joint angle estimates generally remain below 5 degrees for all three ankle joint angles and for flexion/extension and abduction/adduction of the hips and knees when compared to estimates from reflective markers on the IMUs. Additionally, mean RMS differences in estimated stride length and step width remain below 0.13 m for all gait types, except stride length during slow walking. This study confirms the method’s potential for non-laboratory based gait analysis, motivating further evaluation with IMU-only measurements and pathological gaits. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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14 pages, 2358 KiB  
Article
Design Validation of a Low-Cost EMG Sensor Compared to a Commercial-Based System for Measuring Muscle Activity and Fatigue
by Anthony Bawa and Konstantinos Banitsas
Sensors 2022, 22(15), 5799; https://doi.org/10.3390/s22155799 - 3 Aug 2022
Cited by 7 | Viewed by 3336
Abstract
Electromyography (EMG) sensors have been used for measuring muscle signals and for diagnosing neuromuscular disease. Available commercial EMG sensor are expensive and not easily available for individuals. The aim of the study is to validate our designed low-cost sensor against a well-known commercial [...] Read more.
Electromyography (EMG) sensors have been used for measuring muscle signals and for diagnosing neuromuscular disease. Available commercial EMG sensor are expensive and not easily available for individuals. The aim of the study is to validate our designed low-cost sensor against a well-known commercial system for measuring muscle activity and fatigue assessment. The evaluation of the designed system was done through a series of dynamic exercises performed by volunteers. Our low-cost EMG sensor and the commercially available system were placed on the vastus lateralis muscle to concurrently record the signal in a maximum voluntary contraction (MVC). The signal analysis was done using two validation indicators: Spearman’s correlation, and intra-class cross correlation on SPSS 26.0 version. For the muscle fatigue assessment, the root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) indicators were used. The results at the peak and mean level muscle contraction intensity were computed. The relative agreement for the two systems was excellent at peak level muscle contraction range (ICC 0.74–0.92), average 0.83 and mean level muscle contraction intensity range (ICC 0.65–0.85) with an average of 0.74. The Spearman’s correlation average was 0.76 with the range of (0.71–0.85) at peak level contraction, whiles the mean level contraction average was 0.71 at a range of (0.62–0.81). In determining muscle fatigue, the RMS and MAV showed increasing values in the time domain, while the MEF decreased in the frequency domain. Overall, the results indicated a good to excellent agreement of the two systems and confirmed the reliability of our design. The low-cost sensor also proved to be suitable for muscle fatigue assessment. Our designed system can therefore be implemented for rehabilitation, sports science, and ergonomics. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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Review

Jump to: Research, Other

29 pages, 6104 KiB  
Review
Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review
by Xinxin Huang, Yunan Xue, Shuyun Ren and Fei Wang
Sensors 2023, 23(22), 9047; https://doi.org/10.3390/s23229047 - 8 Nov 2023
Cited by 1 | Viewed by 2649
Abstract
In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and [...] Read more.
In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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15 pages, 527 KiB  
Review
Kinect-Based Assessment of Lower Limbs during Gait in Post-Stroke Hemiplegic Patients: A Narrative Review
by Serena Cerfoglio, Claudia Ferraris, Luca Vismara, Gianluca Amprimo, Lorenzo Priano, Giuseppe Pettiti, Manuela Galli, Alessandro Mauro and Veronica Cimolin
Sensors 2022, 22(13), 4910; https://doi.org/10.3390/s22134910 - 29 Jun 2022
Cited by 15 | Viewed by 2923
Abstract
The aim of this review was to present an overview of the state of the art in the use of the Microsoft Kinect camera to assess gait in post-stroke individuals through an analysis of the available literature. In recent years, several studies have [...] Read more.
The aim of this review was to present an overview of the state of the art in the use of the Microsoft Kinect camera to assess gait in post-stroke individuals through an analysis of the available literature. In recent years, several studies have explored the potentiality, accuracy, and effectiveness of this 3D optical sensor as an easy-to-use and non-invasive clinical measurement tool for the assessment of gait parameters in several pathologies. Focusing on stroke individuals, some of the available studies aimed to directly assess and characterize their gait patterns. In contrast, other studies focused on the validation of Kinect-based measurements with respect to a gold-standard reference (i.e., optoelectronic systems). However, the nonhomogeneous characteristics of the participants, of the measures, of the methodologies, and of the purposes of the studies make it difficult to adequately compare the results. This leads to uncertainties about the strengths and weaknesses of this technology in this pathological state. The final purpose of this narrative review was to describe and summarize the main features of the available works on gait in the post-stroke population, highlighting similarities and differences in the methodological approach and primary findings, thus facilitating comparisons of the studies as much as possible. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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30 pages, 626 KiB  
Systematic Review
Physical Activity in Community-Dwelling Older Adults: Which Real-World Accelerometry Measures Are Robust? A Systematic Review
by Khalid Abdul Jabbar, Ríona Mc Ardle, Sue Lord, Ngaire Kerse, Silvia Del Din and Ruth Teh
Sensors 2023, 23(17), 7615; https://doi.org/10.3390/s23177615 - 2 Sep 2023
Viewed by 1042
Abstract
Measurement of real-world physical activity (PA) data using accelerometry in older adults is informative and clinically relevant, but not without challenges. This review appraises the reliability and validity of accelerometry-based PA measures of older adults collected in real-world conditions. Eight electronic databases were [...] Read more.
Measurement of real-world physical activity (PA) data using accelerometry in older adults is informative and clinically relevant, but not without challenges. This review appraises the reliability and validity of accelerometry-based PA measures of older adults collected in real-world conditions. Eight electronic databases were systematically searched, with 13 manuscripts included. Intraclass correlation coefficient (ICC) for inter-rater reliability were: walking duration (0.94 to 0.95), lying duration (0.98 to 0.99), sitting duration (0.78 to 0.99) and standing duration (0.98 to 0.99). ICCs for relative reliability ranged from 0.24 to 0.82 for step counts and 0.48 to 0.86 for active calories. Absolute reliability ranged from 5864 to 10,832 steps and for active calories from 289 to 597 kcal. ICCs for responsiveness for step count were 0.02 to 0.41, and for active calories 0.07 to 0.93. Criterion validity for step count ranged from 0.83 to 0.98. Percentage of agreement for walking ranged from 63.6% to 94.5%; for lying 35.6% to 100%, sitting 79.2% to 100%, and standing 38.6% to 96.1%. Construct validity between step count and criteria for moderate-to-vigorous PA was rs = 0.68 and 0.72. Inter-rater reliability and criterion validity for walking, lying, sitting and standing duration are established. Criterion validity of step count is also established. Clinicians and researchers may use these measures with a limited degree of confidence. Further work is required to establish these properties and to extend the repertoire of PA measures beyond “volume” counts to include more nuanced outcomes such as intensity of movement and duration of postural transitions. Full article
(This article belongs to the Special Issue Wearable or Markerless Sensors for Gait and Movement Analysis)
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