Wearable technologiesPub Date : 2022-11-23eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.25
Katelyn Fry-Hilderbrand, Yu-Ping Chen, Ayanna Howard
{"title":"Automated assessment of infant motor development to predict infant age: The determination of objective metrics of spontaneous kicking.","authors":"Katelyn Fry-Hilderbrand, Yu-Ping Chen, Ayanna Howard","doi":"10.1017/wtc.2022.25","DOIUrl":"10.1017/wtc.2022.25","url":null,"abstract":"<p><p>Though early intervention can improve outcomes for children with motor disabilities, delays in diagnosis can impact the success of intervention programs. Prior work indicates that spontaneous kicking patterns can be used to model typical infant motor development to assist in the early detection of motor delays. However, abnormalities in spontaneous movements are not well defined or readily observable through traditional functional assessments. In this research, a method is introduced for the early detection of delays through the assessment of spontaneous kicking data gathered using a wearable sensing suit. We present formulations of kinematic features identified in the clinical space, identify which features are significant predictors of infant age, and establish normative values. Finally, we offer an analysis of preterm (PT) infant data compared to normative values derived from term infants. Term and PT infants ranging in age from 1 to 10 months were studied. We found that frequency, duration, acceleration, inter-joint coordination, and maximum joint excursion metrics had a significant correlation with age. From these features, models of typical kicking development were created using data from term, typically developing infants. When compared to normative trends, PT infants display differing developmental trends.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48400076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-10-25eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.23
Qingya Zhao, Zhuo Chen, Corey D Landis, Ashley Lytle, Ashwini K Rao, Damiano Zanotto, Yi Guo
{"title":"Gait monitoring for older adults during guided walking: An integrated assistive robot and wearable sensor approach.","authors":"Qingya Zhao, Zhuo Chen, Corey D Landis, Ashley Lytle, Ashwini K Rao, Damiano Zanotto, Yi Guo","doi":"10.1017/wtc.2022.23","DOIUrl":"10.1017/wtc.2022.23","url":null,"abstract":"<p><p>An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41279169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Erratum: Wearables in sociodrama: An embodied mixed-methods study of expressiveness in social interactions-CORRIGENDUM.","authors":"Katerina El-Raheb, Vilelmini Kalampratsidou, Philia Issari, Eugenie Georgaca, Flora Koliouli, Evangelia Karydi, Theodora Dora Skali, Pandelis Diamantides, Yannis Ioannidis","doi":"10.1017/wtc.2022.24","DOIUrl":"10.1017/wtc.2022.24","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1017/wtc.2022.7.].</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48453981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-10-12eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.21
Joshua Ong, Nasif Zaman, Ethan Waisberg, Sharif Amit Kamran, Andrew G Lee, Alireza Tavakkoli
{"title":"Head-mounted digital metamorphopsia suppression as a countermeasure for macular-related visual distortions for prolonged spaceflight missions and terrestrial health.","authors":"Joshua Ong, Nasif Zaman, Ethan Waisberg, Sharif Amit Kamran, Andrew G Lee, Alireza Tavakkoli","doi":"10.1017/wtc.2022.21","DOIUrl":"10.1017/wtc.2022.21","url":null,"abstract":"<p><p>During long-duration spaceflight, astronauts are exposed to various risks including spaceflight-associated neuro-ocular syndrome, which serves as a risk to astronaut vision and a potential physiological barrier to future spaceflight. When considering exploration missions that may expose astronauts to longer periods of microgravity, radiation exposure, and natural aging processes during spaceflight, more severe changes to functional vision may occur. The macula plays a critical role in central vision and disruptions to this key area in the eye may compromise functional vision and mission performance. In this article, we describe the development of a countermeasure technique to digitally suppress monocular central visual distortion with head-mounted display technology. We report early validation studies with this noninvasive countermeasure in individuals with simulated metamorphopsia. When worn by these individuals, this emerging wearable countermeasure technology has demonstrated a suppression of monocular visual distortion. We describe the considerations and further directions of this head-mounted technology for both astronauts and aging individuals on Earth.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43633932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-10-03eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.22
Chiharu Ishii, Kanta Hirasawa
{"title":"The effect of a movable headrest in shoulder assist device for overhead work.","authors":"Chiharu Ishii, Kanta Hirasawa","doi":"10.1017/wtc.2022.22","DOIUrl":"10.1017/wtc.2022.22","url":null,"abstract":"<p><p>Recently, many kinds of shoulder-support exoskeletons have been developed and some of them are commercially available. However, to the best of our knowledge, shoulder-support exoskeletons that have neck-support mechanism have not been found. During the overhead work, physical strain is added to not only upper limb and shoulder but also neck of workers since the workers work keeping their face raised. Therefore, in this study, to reduce the physical strain on the neck during the overhead work, a movable headrest that can be attached to the shoulder assist device was developed, which has reclining and slide functions of a head. The main purpose of this article was to evaluate usefulness of the proposed movable headrest. To this end, measurements of electromyogram were carried out under simulating an overhead work activity, and the reduction effect for physical strain of the neck was compared among three types of headrests: (a) slide-type headrest which can slide the head backward and forward, (b) reclining-type headrest which can recline the head, and (c) reclining and slide-type headrest which can recline and slide the head. In addition, usefulness of the shoulder assist device with the proposed headrest was evaluated for a realistic overhead work activity through measurements of muscular stiffness of neck and shoulder. The experimental results showed that the existence of the headrest in the shoulder assist device is effective to reduce the physical strain to the workers, and that (c) reclining and slide-type headrest is the most effective among these three types of headrests.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42099635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exoworkathlon: A prospective study approach for the evaluation of industrial exoskeletons.","authors":"Verena Kopp, Mirjam Holl, Marco Schalk, Urban Daub, Enrique Bances, Braulio García, Ines Schalk, Jörg Siegert, Urs Schneider","doi":"10.1017/wtc.2022.17","DOIUrl":"10.1017/wtc.2022.17","url":null,"abstract":"<p><p>Industrial exoskeletons have recently gained importance as ergonomic interventions for physically demanding work activities. The growing demand for exoskeletons is leading to a need for new knowledge on the effectiveness of these systems. The Exoworkathlon, as a prospective study approach, aims to assess exoskeletons in realistic use cases and to evaluate them neutrally in their entirety. For this purpose, a first set of four realistic Parcours was developed with experts from relevant industries, the German Social Accident Insurance, and the Federal Institute for Occupational Safety and Health. In addition, a set of ratings was defined to assess subjective user feedback, work quality, and objective physiological parameters. Exoworkathlon aims to bring together developers, researchers, and end-users, strengthen collaborative exchanges, and promote a platform for the prospective holistic data collection for exoskeleton evaluation. In this article, the focus is on the background and methodology of Exoworkathlon.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936367/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44585932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-09-19eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.20
Jason C Gillette, Shekoofe Saadat, Terry Butler
{"title":"Electromyography-based fatigue assessment of an upper body exoskeleton during automotive assembly.","authors":"Jason C Gillette, Shekoofe Saadat, Terry Butler","doi":"10.1017/wtc.2022.20","DOIUrl":"10.1017/wtc.2022.20","url":null,"abstract":"<p><p>The purpose of this study was to assess an upper body exoskeleton during automotive assembly processes that involve elevated arm postures. Sixteen team members at Toyota Motor Manufacturing Canada were fitted with a Levitate Airframe, and each team member performed between one and three processes with and without the exoskeleton. A total of 16 assembly processes were studied. Electromyography (EMG) data were collected on the anterior deltoid, biceps brachii, upper trapezius, and erector spinae. Team members also completed a usability survey. The exoskeleton significantly reduced anterior deltoid mean active EMG amplitude (<i>p</i> = .01, Δ = -3.2 %MVC, <i>d</i> = 0.56 medium effect) and fatigue risk value (<i>p</i> < .01, Δ = -5.1 %MVC, <i>d</i> = 0.62 medium effect) across the assembly processes, with no significant changes for the other muscles tested. A subset of nine assembly processes with a greater amount of time spent in arm elevations at or above 90° (30 vs. 24%) and at or above 135° (18 vs. 9%) appeared to benefit more from exoskeleton usage. For these processes, the exoskeleton significantly reduced anterior deltoid mean active EMG amplitude (<i>p</i> < .01, Δ = -5.1 %MVC, <i>d</i> = 0.95 large effect) and fatigue risk value (<i>p</i> < .01, Δ = -7.4 %MVC, <i>d</i> = 0.96 large effect). Team members responded positively about comfort and fatigue benefits, although there were concerns about the exoskeleton hindering certain job duties. The results support quantitative testing to match exoskeleton usage with specific job tasks and surveying team members for perceived benefits/drawbacks.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42641364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A deep learning method to predict ankle joint moment during walking at different speeds with ultrasound imaging: A framework for assistive devices control.","authors":"Qiang Zhang, Natalie Fragnito, Xuefeng Bao, Nitin Sharma","doi":"10.1017/wtc.2022.18","DOIUrl":"10.1017/wtc.2022.18","url":null,"abstract":"<p><p>Robotic assistive or rehabilitative devices are promising aids for people with neurological disorders as they help regain normative functions for both upper and lower limbs. However, it remains challenging to accurately estimate human intent or residual efforts non-invasively when using these robotic devices. In this article, we propose a deep learning approach that uses a brightness mode, that is, B-mode, of ultrasound (US) imaging from skeletal muscles to predict the ankle joint net plantarflexion moment while walking. The designed structure of customized deep convolutional neural networks (CNNs) guarantees the convergence and robustness of the deep learning approach. We investigated the influence of the US imaging's region of interest (ROI) on the net plantarflexion moment prediction performance. We also compared the CNN-based moment prediction performance utilizing B-mode US and sEMG spectrum imaging with the same ROI size. Experimental results from eight young participants walking on a treadmill at multiple speeds verified an improved accuracy by using the proposed US imaging + deep learning approach for net joint moment prediction. With the same CNN structure, compared to the prediction performance by using sEMG spectrum imaging, US imaging significantly reduced the normalized prediction root mean square error by 37.55% ( < .001) and increased the prediction coefficient of determination by 20.13% ( < .001). The findings show that the US imaging + deep learning approach personalizes the assessment of human joint voluntary effort, which can be incorporated with assistive or rehabilitative devices to improve clinical performance based on the assist-as-needed control strategy.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46798225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-08-17eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.15
Doga Cavdir, Ge Wang
{"title":"Designing felt experiences with movement-based, wearable musical instruments: From inclusive practices toward participatory design.","authors":"Doga Cavdir, Ge Wang","doi":"10.1017/wtc.2022.15","DOIUrl":"10.1017/wtc.2022.15","url":null,"abstract":"<p><p>Inclusive musical instruments benefit from incorporating wearable interfaces into digital musical instrument design, creating opportunities for bodily felt experiences and movement-based interactions. In this article, we discuss the evolution of our inclusive design approach behind the design and performance practices of three wearable musical instruments. By focusing on the embodied, somatic, and tacit dimensions of movement-based musical interaction, we evaluate these case studies, combining the third and first-person perspectives. The design and implementation of the wearable sensing, utilizing the additive manufacturing techniques, are discussed for each instrument and its performer in specific cases of musical expression. This article further discusses how our approach integrates music performance as a crucial step into design and evaluation, utilizing these performance practices and such collaborative settings for improved diversity and inclusion. Finally, we examine how our design approach evolves from user-centered design to more participatory practices, offering people with diverse abilities a shared music performance space.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936373/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49118204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable technologiesPub Date : 2022-07-20eCollection Date: 2022-01-01DOI: 10.1017/wtc.2022.13
Marco Schalk, Ines Schalk, Thomas Bauernhansl, Jörg Siegert, Alexander Esin, Urs Schneider
{"title":"Influence of exoskeleton use on welding quality during a simulated welding task.","authors":"Marco Schalk, Ines Schalk, Thomas Bauernhansl, Jörg Siegert, Alexander Esin, Urs Schneider","doi":"10.1017/wtc.2022.13","DOIUrl":"10.1017/wtc.2022.13","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study is to investigate the effects of wearing exoskeletons during welding on the quality of the weld seam.</p><p><strong>Material and methods: </strong>A total of <i>n</i> = 15 young healthy subjects with welding experience took part in the study. The study design defines a 1-hr workflow that abstracts welding and grinding tasks. The sequence is based on standard DIN EN ISO 9606-1 and reproduces authentic work sequences in the constrained body positions PF-workpiece in front of the body and PE-workpiece overhead. Each subject completed the entire workflow once with and once without passive shoulder exoskeleton in a randomized order.</p><p><strong>Results: </strong>The evaluation shows that the use of passive shoulder exoskeletons has a significant influence (<i>p</i> = .006 for Position PF; <i>p</i> = .029 for Position PE) on the welding parameter travel speed which significantly influences the quality of the weld seam. The quality scale (by the used augmented reality (AR) welding simulator) of the travel speed, which significantly determines the permissibility of the weld, increases by 5.80% in the constrained body position PF and by 28.87% in the constrained body position PE when using an exoskeleton.</p><p><strong>Discussion and conclusion: </strong>The score of the welding parameter travel speed, which is essential for the permissibility of the seam, shows a statistically significant increase when an assistance system is used. Further research during real welding with exoskeletons could be based on the setup and workflow of this study.</p>","PeriodicalId":75318,"journal":{"name":"Wearable technologies","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47276399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}