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Advanced Sensors in Biomechanics and Rehabilitation

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 20236

Special Issue Editor


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Guest Editor
School of Biological and Health Systems Engineering, Ira A Fulton Schools of Engineering, Arizona State University, Tempe, AZ, USA
Interests: gait and posture; activity monitoring; fall risk assessment; nonlinear dynamics; biodynamics; wireless inertial sensors; wearables; musculoskeletal and neuro-rehabilitation
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Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to unraveling the transformative role of sensor technologies in the field of biomechanics and rehabilitation. In an era where precision and personalized care are paramount, these sophisticated tools significantly enhance our ability to understand human motion mechanics and develop effective therapeutic interventions.

The adoption of sensors in biomechanical studies allows for detailed analyses of body posture, gait, muscle activation, and joint kinematics, leading to more accurate diagnoses and tailored treatments. Moreover, in the context of rehabilitation, sensors facilitate the real-time tracking of patients' functional abilities, thus informing clinicians on the efficacy of therapeutic approaches and guiding necessary adjustments. Wearable sensors, for instance, can provide valuable insights into patients' daily activities, helping determine the effectiveness of prescribed exercises and further enhancing rehabilitation outcomes.

This Special Issue aims to shed light on current research exploring the application of sensing technology in biomechanics and rehabilitation. We invite you to submit original research papers to the issue.

You may choose our Joint Special Issue in J.

Prof. Dr. Thurmon Lockhart
Guest Editor

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Keywords

  • wearable sensors
  • biomechanics
  • rehabilitation
  • gait analysis
  • posture

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Published Papers (15 papers)

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Research

13 pages, 2228 KiB  
Article
The Minimum Number of Strides Required for Reliable Gait Measurements in Older Adult Fallers and Non-Fallers
by Drew Commandeur, Marc Klimstra, Kaya Yoshida and Sandra Hundza
Sensors 2024, 24(23), 7666; https://doi.org/10.3390/s24237666 - 30 Nov 2024
Viewed by 330
Abstract
While the value of walking gait metrics collected using pressure-sensing walkways has shown promise for fall risk assessment, there is no consensus on the minimum number of strides required to obtain reliable metrics. This study aimed to determine the minimum stride count required [...] Read more.
While the value of walking gait metrics collected using pressure-sensing walkways has shown promise for fall risk assessment, there is no consensus on the minimum number of strides required to obtain reliable metrics. This study aimed to determine the minimum stride count required for reliable single-task (ST), dual-task (DT), and difference score (DS) measurements of the spatio-temporal parameters of gait in older adult fallers and non-fallers. Forty community-dwelling older adults (74.6 ± 3.5 years) performed 10 ST and 10 DT walking passes (~100 strides total) across a GAITRite™ pressure mat. Nine truncated datasets (1–9 passes) were created from the original for each walking condition to assess agreement using two-way random effects, absolute agreement, and single-rater intraclass correlations (ICCs). ICCs demonstrated that a minimum of one pass (~10 strides) is sufficient for reliable mean gait metrics for ST and DT conditions and 10–30 strides for DS, while 10–80 strides are needed for reliable gait variability measures, depending on the metric. This study provides stride count recommendations to ensure reliable gait measurement in older adult populations, highlighting that as few as 10–30 strides are necessary for mean metrics, while variability metrics may require up to 80 strides to ensure reliability. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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20 pages, 8072 KiB  
Article
Using a Webcam to Assess Upper Extremity Proprioception: Experimental Validation and Application to Persons Post Stroke
by Guillem Cornella-Barba, Andria J. Farrens, Christopher A. Johnson, Luis Garcia-Fernandez, Vicky Chan and David J. Reinkensmeyer
Sensors 2024, 24(23), 7434; https://doi.org/10.3390/s24237434 - 21 Nov 2024
Viewed by 523
Abstract
Many medical conditions impair proprioception but there are few easy-to-deploy technologies for assessing proprioceptive deficits. Here, we developed a method—called “OpenPoint”—to quantify upper extremity (UE) proprioception using only a webcam as the sensor. OpenPoint automates a classic neurological test: the ability of a [...] Read more.
Many medical conditions impair proprioception but there are few easy-to-deploy technologies for assessing proprioceptive deficits. Here, we developed a method—called “OpenPoint”—to quantify upper extremity (UE) proprioception using only a webcam as the sensor. OpenPoint automates a classic neurological test: the ability of a person to use one hand to point to a finger on their other hand with vision obscured. Proprioception ability is quantified with pointing error in the frontal plane measured by a deep-learning-based, computer vision library (MediaPipe). In a first experiment with 40 unimpaired adults, pointing error significantly increased when we replaced the target hand with a fake hand, verifying that this task depends on the availability of proprioceptive information from the target hand, and that we can reliably detect this dependence with computer vision. In a second experiment, we quantified UE proprioceptive ability in 16 post-stroke participants. Individuals post stroke exhibited increased pointing error (p < 0.001) that was correlated with finger proprioceptive error measured with an independent, robotic assessment (r = 0.62, p = 0.02). These results validate a novel method to assess UE proprioception ability using affordable computer technology, which provides a potential means to democratize quantitative proprioception testing in clinical and telemedicine environments. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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12 pages, 1118 KiB  
Article
Influence of Bladder Filling on Parameters of Body Composition by Bioimpedance Electrical Analysis: Observational Study
by Asunción Ferri-Morales, Sara Ando-Lafuente, Cristina Lirio-Romero, Emanuele Marzetti and Elisabeth Bravo-Esteban
Sensors 2024, 24(22), 7343; https://doi.org/10.3390/s24227343 - 18 Nov 2024
Viewed by 514
Abstract
Bioelectrical impedance analysis (BIA) is a widely used method for estimating body composition, and its accuracy may be influenced by various factors, including bladder filling. This study aims to investigate the impact of bladder filling on the accuracy of BIA measurements. An experimental [...] Read more.
Bioelectrical impedance analysis (BIA) is a widely used method for estimating body composition, and its accuracy may be influenced by various factors, including bladder filling. This study aims to investigate the impact of bladder filling on the accuracy of BIA measurements. An experimental crossover study was conducted with sedentary young adults. The influence of bladder filling on total body water (TBW), fat mass (FM), fat-free mass (FFM), and basal metabolic rate (BMR) was assessed. Participant in underwear followed an overnight fast. They were instructed to abstain from vigorous physical activity and alcohol for at least 24 h prior to the session. The results obtained from single-frequency and multi-frequency BIA devices were compared. The findings suggest that bladder filling does not affect measured impedance; however, changes in weight following bladder voiding influenced derived BIA results. Specifically, TBW, FM, and BMR values significantly reduced after voiding (p < 0.05). Furthermore, the study found poor agreement between single-frequency and multi-frequency BIA devices, indicating that they are not interchangeable. Bladder filling does affect BIA measurements, not clinically meaningful. Further research is needed to explore the implications of these findings for clinical practice and research protocols. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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14 pages, 2349 KiB  
Article
Effects of Mild Fatigue on Biomechanics of Single Leg Landing in Young Male Volleyball Players
by Taisen Li, Leonid Vladimirovich Kapilevich and Junru Chen
Sensors 2024, 24(21), 6811; https://doi.org/10.3390/s24216811 - 23 Oct 2024
Viewed by 788
Abstract
Objective: To investigate the effects of mild fatigue on the biomechanics of the lower limbs of young male volleyball players while performing single leg landing tasks. Methods: A total of ten young male volleyball players were recruited as participants in this study. After [...] Read more.
Objective: To investigate the effects of mild fatigue on the biomechanics of the lower limbs of young male volleyball players while performing single leg landing tasks. Methods: A total of ten young male volleyball players were recruited as participants in this study. After the single leg landing was performed, we compared the performance between those with and without fatigue (post- and non-fatigue, respectively). Kinematics and kinetics were collected using instruments, and related captured data were imported into OpenSim to analyze the hip, knee, and ankle joints. Results: We found that the ankle dorsiflexion angle at initial contact was significantly decreased in the post-fatigue group compared to the non-fatigue one. Meanwhile, the peak gluteus maximus force, peak gluteus medius force, peak tibialis posterior force, and peak gastrocnemius force significantly increased. There were no significant differences in the hip and knee joint flexion angles as well as the quadriceps and biceps femoris long head forces between the two groups. Conclusions: Mild fatigue can affect the performance of single leg landing, and players need to control the lower limbs by generating a higher muscle force to cope with the instability induced by fatigue. In a fatigued state, following initial contact with the ground, a decreased ankle dorsiflexion angle necessitates an increase in gastrocnemius and tibialis posterior muscle force to maintain stance during landing. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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12 pages, 1362 KiB  
Article
Muscle Tone Assessment by Machine Learning Using Surface Electromyography
by Andressa Rastrelo Rezende, Camille Marques Alves, Isabela Alves Marques, Luciane Aparecida Pascucci Sande de Souza and Eduardo Lázaro Martins Naves
Sensors 2024, 24(19), 6362; https://doi.org/10.3390/s24196362 - 30 Sep 2024
Viewed by 859
Abstract
Muscle tone is defined as the resistance to passive stretch, but this definition is often criticized for its ambiguity since some suggest it is related to a state of preparation for movement. Muscle tone is primarily regulated by the central nervous system, and [...] Read more.
Muscle tone is defined as the resistance to passive stretch, but this definition is often criticized for its ambiguity since some suggest it is related to a state of preparation for movement. Muscle tone is primarily regulated by the central nervous system, and individuals with neurological disorders may lose the ability to control normal tone and can exhibit abnormalities. Currently, these abnormalities are mostly evaluated using subjective scales, highlighting a lack of objective assessment methods in the literature. This study aimed to use surface electromyography (sEMG) and machine learning (ML) for the objective classification and characterization of the full spectrum of muscle tone in the upper limb. Data were collected from thirty-nine individuals, including spastic, healthy, hypotonic and rigid subjects. All of the classifiers applied achieved high accuracy, with the best reaching 96.12%, in differentiating muscle tone. These results underscore the potential of the proposed methodology as a more reliable and quantitative method for evaluating muscle tone abnormalities, aiming to address the limitations of traditional subjective assessments. Additionally, the main features impacting the classifiers’ performance were identified, which can be utilized in future research and in the development of devices that can be used in clinical practice. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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16 pages, 1463 KiB  
Article
Effect of Sampling Rate, Filtering, and Torque Onset Detection on Quadriceps Rate of Torque Development and Torque Steadiness
by McKenzie S. White, Megan C. Graham, Tereza Janatova, Gregory S. Hawk, Katherine L. Thompson and Brian Noehren
Sensors 2024, 24(13), 4250; https://doi.org/10.3390/s24134250 - 30 Jun 2024
Viewed by 1174
Abstract
Quadriceps rate of torque development (RTD) and torque steadiness are valuable metrics for assessing explosive strength and the ability to control force over a sustained period of time, which can inform clinical assessments of knee function. Despite their widespread use, there is a [...] Read more.
Quadriceps rate of torque development (RTD) and torque steadiness are valuable metrics for assessing explosive strength and the ability to control force over a sustained period of time, which can inform clinical assessments of knee function. Despite their widespread use, there is a significant gap in standardized methodology for measuring these metrics, which limits their utility in comparing outcomes across different studies and populations. To address these gaps, we evaluated the influence of sampling rates, signal filtering, and torque onset detection on RTD and torque steadiness. Twenty-seven participants with a history of a primary anterior cruciate ligament reconstruction (N = 27 (11 male/16 female), age = 23 ± 8 years, body mass index = 26 ± 4 kg/m2) and thirty-two control participants (N = 32 (13 male/19 female), age = 23 ± 7 years, body mass index = 23 ± 3 kg/m2) underwent isometric quadriceps strength testing, with data collected at 2222 Hz on an isokinetic dynamometer. The torque–time signal was downsampled to approximately 100 and 1000 Hz and processed using a low-pass, zero-lag Butterworth filter with a range of cutoff frequencies spanning 10–200 Hz. The thresholds used to detect torque onset were defined as 0.1 Nm, 1 Nm, and 5 Nm. RTD between 0 and 100 ms, 0 and 200 ms, and 40–160 ms was computed, as well as absolute and relative torque steadiness. Relative differences were computed by comparing all outcomes to the “gold standard” values computed, with a sampling rate of 2222 Hz, a cutoff frequency in the low-pass filter of 150 Hz, and torque onset of 1 Nm, and compared utilizing linear mixed models. While all combinations of signal collection and processing parameters reached statistical significance (p < 0.05), these differences were consistent between injured and control limbs. Additionally, clinically relevant differences (+/−10%) were primarily observed through torque onset detection methods and primarily affected RTD between 0 and 100 ms. Although measurements of RTD and torque steadiness were generally robust against diverse signal collection and processing parameters, the selection of torque onset should be carefully considered, especially in early RTD assessments that have shorter time epochs. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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15 pages, 1554 KiB  
Article
The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability
by Pnina Marom, Michael Brik, Nirit Agay, Rachel Dankner, Zoya Katzir, Naama Keshet and Dana Doron
Sensors 2024, 24(11), 3594; https://doi.org/10.3390/s24113594 - 2 Jun 2024
Viewed by 1363
Abstract
An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower [...] Read more.
An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen’s d, comparing the application’s readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89–1) and good-to-excellent reliability (ICC range, 0.77–1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58–1). Only ‘step length of the impaired leg’ showed poor-to-good validity (range, 0.37–0.84). Cohen’s d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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11 pages, 4545 KiB  
Communication
Testing Dynamic Balance in People with Multiple Sclerosis: A Correlational Study between Standard Posturography and Robotic-Assistive Device
by Jessica Podda, Giorgia Marchesi, Alice Bellosta, Valentina Squeri, Alice De Luca, Ludovico Pedullà, Andrea Tacchino and Giampaolo Brichetto
Sensors 2024, 24(11), 3325; https://doi.org/10.3390/s24113325 - 23 May 2024
Cited by 1 | Viewed by 993
Abstract
Background: Robotic devices are known to provide pivotal parameters to assess motor functions in Multiple Sclerosis (MS) as dynamic balance. However, there is still a lack of validation studies comparing innovative technologies with standard solutions. Thus, this study’s aim was to compare the [...] Read more.
Background: Robotic devices are known to provide pivotal parameters to assess motor functions in Multiple Sclerosis (MS) as dynamic balance. However, there is still a lack of validation studies comparing innovative technologies with standard solutions. Thus, this study’s aim was to compare the postural assessment of fifty people with MS (PwMS) during dynamic tasks performed with the gold standard EquiTest® and the robotic platform hunova®, using Center of Pressure (COP)-related parameters and global balance indexes. Methods: Pearson’s ρ correlations were run for each COP-related measure and the global balance index was computed from EquiTest® and hunova® in both open (EO) and closed-eyes (EC) conditions. Results: Considering COP-related parameters, all correlations were significant in both EO (0.337 ≤ ρ ≤ 0.653) and EC (0.344 ≤ ρ ≤ 0.668). Furthermore, Pearson’s analysis of global balance indexes revealed relatively strong for visual and vestibular, and strong for somatosensory system associations (ρ = 0.573; ρ = 0.494; ρ = 0.710, respectively). Conclusions: Findings confirm the use of hunova® as a valid device for dynamic balance assessment in MS, suggesting that such a robotic platform could allow for a more sensitive assessment of balance over time, and thus a better evaluation of the effectiveness of personalized treatment, thereby improving evidence-based clinical practice. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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11 pages, 1172 KiB  
Article
A Statistical and AI Analysis of the Frequency Spectrum in the Measurement of the Center of Pressure Track in the Seated Position in Healthy Subjects and Subjects with Low Back Pain
by Jan Jens Koltermann, Philipp Floessel, Franziska Hammerschmidt and Alexander C. Disch
Sensors 2024, 24(10), 3011; https://doi.org/10.3390/s24103011 - 9 May 2024
Viewed by 814
Abstract
Measuring postural control in an upright standing position is the standard method. However, this diagnostic method has floor or ceiling effects and its implementation is only possible to a limited extent. Assessing postural control directly on the trunk in a sitting position and [...] Read more.
Measuring postural control in an upright standing position is the standard method. However, this diagnostic method has floor or ceiling effects and its implementation is only possible to a limited extent. Assessing postural control directly on the trunk in a sitting position and consideration of the results in the spectrum in conjunction with an AI-supported evaluation could represent an alternative diagnostic method quantifying neuromuscular control. In a prospective cross-sectional study, 188 subjects aged between 18 and 60 years were recruited and divided into two groups: “LowBackPain” vs. “Healthy”. Subsequently, measurements of postural control in a seated position were carried out for 60 s using a modified balance board. A spectrum per trail was calculated using the measured CoP tracks in the range from 0.01 to 10 Hz. Various algorithms for data classification and prediction of these classes were tested for the parameter combination with the highest proven static influence on the parameter pain. The best results were found in a frequency spectrum of 0.001 Hz and greater than 1 Hz. After transforming the track from the time domain to the image domain for representation as power density, the influence of pain was highly significant (effect size 0.9). The link between pain and gender (p = 0.015) and pain and height (p = 0.012) also demonstrated significant results. The assessment of postural control in a seated position allows differentiation between “LowBackPain” and “Healthy” subjects. Using the AI algorithm of neural networks, the data set can be correctly differentiated into “LowBackPain” and “Healthy” with a probability of 81%. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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10 pages, 1233 KiB  
Article
Evaluating Postural Transition Movement Performance in Individuals with Essential Tremor via the Instrumented Timed Up and Go
by Patrick G. Monaghan, William M. Murrah, Harrison C. Walker, Kristina A. Neely and Jaimie A. Roper
Sensors 2024, 24(7), 2216; https://doi.org/10.3390/s24072216 - 29 Mar 2024
Viewed by 1033
Abstract
Flexibility in performing various movements like standing, walking, and turning is crucial for navigating dynamic environments in daily life. Individuals with essential tremor often experience movement difficulties that can affect these postural transitions, limiting mobility and independence. Yet, little research has examined the [...] Read more.
Flexibility in performing various movements like standing, walking, and turning is crucial for navigating dynamic environments in daily life. Individuals with essential tremor often experience movement difficulties that can affect these postural transitions, limiting mobility and independence. Yet, little research has examined the performance of postural transitions in people with essential tremor. Therefore, we assessed postural transition performance using two versions of the timed up and go test: the standard version and a more complex water-carry version. We examined the total duration of the standard and water-carry timed up and go in 15 people with and 15 people without essential tremor. We also compared the time taken for each phase (sit-to-stand phase, straight-line walk phase, stand-to-sit phase) and the turning velocity between groups. Our findings revealed decreased performance across all phases of standard and water-carry timed up and go assessments. Further, both ET and non-ET groups exhibited reduced performance during the water-carry timed up and go compared to the standard timed up and go. Evaluating specific phases of the timed up and go offers valuable insights into functional movement performance in essential tremor, permitting more tailored therapeutic interventions to improve functional performance during activities of daily living. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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13 pages, 2683 KiB  
Article
Propulsive Force Modulation Drives Split-Belt Treadmill Adaptation in People with Multiple Sclerosis
by Andrew C. Hagen, Christopher M. Patrick, Isaac E. Bast and Brett W. Fling
Sensors 2024, 24(4), 1067; https://doi.org/10.3390/s24041067 - 6 Feb 2024
Cited by 1 | Viewed by 1546
Abstract
Most people with multiple sclerosis (PwMS) experience significant gait asymmetries between their legs during walking, leading to an increased risk of falls. Split-belt treadmill training, where the speed of each limb is controlled independently, alters each leg’s stepping pattern and can improve gait [...] Read more.
Most people with multiple sclerosis (PwMS) experience significant gait asymmetries between their legs during walking, leading to an increased risk of falls. Split-belt treadmill training, where the speed of each limb is controlled independently, alters each leg’s stepping pattern and can improve gait symmetry in PwMS. However, the biomechanical mechanisms of this adaptation in PwMS remain poorly understood. In this study, 32 PwMS underwent a 10 min split-belt treadmill adaptation paradigm with the more affected (MA) leg moving twice as fast as the less affected (LA) leg. The most noteworthy biomechanical adaptation observed was increased peak propulsion asymmetry between the limbs. A kinematic analysis revealed that peak dorsiflexion asymmetry and the onset of plantarflexion in the MA limb were the primary contributors to the observed increases in peak propulsion. In contrast, the joints in the LA limb underwent only immediate reactive adjustments without subsequent adaptation. These findings demonstrate that modulation during gait adaptation in PwMS occurs primarily via propulsive forces and joint motions that contribute to propulsive forces. Understanding these distinct biomechanical changes during adaptation enhances our grasp of the rehabilitative impact of split-belt treadmill training, providing insights for refining therapeutic interventions aimed at improving gait symmetry. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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11 pages, 4052 KiB  
Article
Reliability and Validity of Shore Hardness in Plantar Soft Tissue Biomechanics
by Redent Tonna, Panagiotis E. Chatzistergos, Otis Wyatt and Nachiappan Chockalingam
Sensors 2024, 24(2), 539; https://doi.org/10.3390/s24020539 - 15 Jan 2024
Cited by 2 | Viewed by 1572
Abstract
Shore hardness (SH) is a cost-effective and easy-to-use method to assess soft tissue biomechanics. Its use for the plantar soft tissue could enhance the clinical management of conditions such as diabetic foot complications, but its validity and reliability remain unclear. Twenty healthy adults [...] Read more.
Shore hardness (SH) is a cost-effective and easy-to-use method to assess soft tissue biomechanics. Its use for the plantar soft tissue could enhance the clinical management of conditions such as diabetic foot complications, but its validity and reliability remain unclear. Twenty healthy adults were recruited for this study. Validity and reliability were assessed across six different plantar sites. The validity was assessed against shear wave (SW) elastography (the gold standard). SH was measured by two examiners to assess inter-rater reliability. Testing was repeated following a test/retest study design to assess intra-rater reliability. SH was significantly correlated with SW speed measured in the skin or in the microchamber layer of the first metatarsal head (MetHead), third MetHead and rearfoot. Intraclass correlation coefficients and Bland–Altman plots of limits of agreement indicated satisfactory levels of reliability for these sites. No significant correlation between SH and SW elastography was found for the hallux, 5th MetHead or midfoot. Reliability for these sites was also compromised. SH is a valid and reliable measurement for plantar soft tissue biomechanics in the first MetHead, the third MetHead and the rearfoot. Our results do not support the use of SH for the hallux, 5th MetHead or midfoot. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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20 pages, 58464 KiB  
Article
Comparison of Shoulder Range of Motion Quantified with Mobile Phone Video-Based Skeletal Tracking and 3D Motion Capture—Preliminary Study
by Wolbert van den Hoorn, Maxence Lavaill, Kenneth Cutbush, Ashish Gupta and Graham Kerr
Sensors 2024, 24(2), 534; https://doi.org/10.3390/s24020534 - 15 Jan 2024
Cited by 3 | Viewed by 2058
Abstract
Background: The accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined. Methods: Twenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation [...] Read more.
Background: The accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined. Methods: Twenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation algorithm (Apple’s vision framework) and using a skin marker-based 3D motion capture system. Validity was assessed by comparing the 2D-pose outcomes against a well-established 3D motion capture protocol. In addition, the impact of iPhone positioning was investigated using three smartphones in multiple vertical and horizontal positions. The relationship and validity were analysed using linear mixed models and Bland-Altman analysis. Results: We found that 2D-pose-based shoulder RoM was consistent with 3D motion capture (linear mixed model: R2 > 0.93) but was somewhat overestimated by the smartphone. Differences were dependent on shoulder movement type and RoM amplitude, with adduction the worst performer among all tested movements. All motion types were described using linear equations. Correction methods are provided to correct potential out-of-plane shoulder movements. Conclusions: Shoulder RoM estimated using a smartphone camera is consistent with 3D motion-capture-derived RoM; however, differences between the systems were observed and are likely explained by differences in thoracic frame definitions. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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23 pages, 990 KiB  
Article
Error Enhancement for Upper Limb Rehabilitation in the Chronic Phase after Stroke: A 5-Day Pre-Post Intervention Study
by Marjan Coremans, Eli Carmeli, Ineke De Bauw, Bea Essers, Robin Lemmens and Geert Verheyden
Sensors 2024, 24(2), 471; https://doi.org/10.3390/s24020471 - 12 Jan 2024
Viewed by 2556
Abstract
A large proportion of chronic stroke survivors still struggle with upper limb (UL) problems in daily activities, typically reaching tasks. During three-dimensional reaching movements, the deXtreme robot offers error enhancement forces. Error enhancement aims to improve the quality of movement. We investigated clinical [...] Read more.
A large proportion of chronic stroke survivors still struggle with upper limb (UL) problems in daily activities, typically reaching tasks. During three-dimensional reaching movements, the deXtreme robot offers error enhancement forces. Error enhancement aims to improve the quality of movement. We investigated clinical and patient-reported outcomes and assessed the quality of movement before and after a 5 h error enhancement training with the deXtreme robot. This pilot study had a pre-post intervention design, recruiting 22 patients (mean age: 57 years, mean days post-stroke: 1571, male/female: 12/10) in the chronic phase post-stroke with UL motor impairments. Patients received 1 h robot treatment for five days and were assessed at baseline and after training, collecting (1) clinical, (2) patient-reported, and (3) kinematic (KINARM, BKIN Technologies Ltd., Kingston, ON, Canada) outcome measures. Our analysis revealed significant improvements (median improvement (Q1–Q3)) in (1) UL Fugl–Meyer assessment (1.0 (0.8–3.0), p < 0.001) and action research arm test (2.0 (0.8–2.0), p < 0.001); (2) motor activity log, amount of use (0.1 (0.0–0.3), p < 0.001) and quality of use (0.1 (0.1–0.5), p < 0.001) subscale; (3) KINARM-evaluated position sense (−0.45 (−0.81–0.09), p = 0.030) after training. These findings provide insight into clinical self-reported and kinematic improvements in UL functioning after five hours of error enhancement UL training. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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13 pages, 1082 KiB  
Article
Explainable Machine Learning Techniques to Predict Muscle Injuries in Professional Soccer Players through Biomechanical Analysis
by Mailyn Calderón-Díaz, Rony Silvestre Aguirre, Juan P. Vásconez, Roberto Yáñez, Matías Roby, Marvin Querales and Rodrigo Salas
Sensors 2024, 24(1), 119; https://doi.org/10.3390/s24010119 - 25 Dec 2023
Cited by 2 | Viewed by 2926
Abstract
There is a significant risk of injury in sports and intense competition due to the demanding physical and psychological requirements. Hamstring strain injuries (HSIs) are the most prevalent type of injury among professional soccer players and are the leading cause of missed days [...] Read more.
There is a significant risk of injury in sports and intense competition due to the demanding physical and psychological requirements. Hamstring strain injuries (HSIs) are the most prevalent type of injury among professional soccer players and are the leading cause of missed days in the sport. These injuries stem from a combination of factors, making it challenging to pinpoint the most crucial risk factors and their interactions, let alone find effective prevention strategies. Recently, there has been growing recognition of the potential of tools provided by artificial intelligence (AI). However, current studies primarily concentrate on enhancing the performance of complex machine learning models, often overlooking their explanatory capabilities. Consequently, medical teams have difficulty interpreting these models and are hesitant to trust them fully. In light of this, there is an increasing need for advanced injury detection and prediction models that can aid doctors in diagnosing or detecting injuries earlier and with greater accuracy. Accordingly, this study aims to identify the biomarkers of muscle injuries in professional soccer players through biomechanical analysis, employing several ML algorithms such as decision tree (DT) methods, discriminant methods, logistic regression, naive Bayes, support vector machine (SVM), K-nearest neighbor (KNN), ensemble methods, boosted and bagged trees, artificial neural networks (ANNs), and XGBoost. In particular, XGBoost is also used to obtain the most important features. The findings highlight that the variables that most effectively differentiate the groups and could serve as reliable predictors for injury prevention are the maximum muscle strength of the hamstrings and the stiffness of the same muscle. With regard to the 35 techniques employed, a precision of up to 78% was achieved with XGBoost, indicating that by considering scientific evidence, suggestions based on various data sources, and expert opinions, it is possible to attain good precision, thus enhancing the reliability of the results for doctors and trainers. Furthermore, the obtained results strongly align with the existing literature, although further specific studies about this sport are necessary to draw a definitive conclusion. Full article
(This article belongs to the Special Issue Advanced Sensors in Biomechanics and Rehabilitation)
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