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Wearable Technology and Movement Analysis in Athletic Performance and Rehabilitation
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Wearable Technology and Movement Analysis in Athletic Performance and Rehabilitation

A special issue of Journal of Functional Morphology and Kinesiology (ISSN 2411-5142). This special issue belongs to the section "Kinesiology and Biomechanics".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1948

Special Issue Editor

Dr. Juri Taborri

E-Mail Website
Guest Editor
Department of Economics, Engineering, Society and Business Organization, University of Tuscia, 01100 Viterbo, Italy
Interests: virtual reality; artificial intelligence; metrology; inclusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the application of wearable sensors and motion analysis tools as a means of deepening our understanding of human movement, optimizing physical performance, and enhancing rehabilitation outcomes. This Issue aims to showcase how movement analysis and performance monitoring are being applied to real-world challenges in sports and clinical rehabilitation.

We welcome contributions that use motion analysis to evaluate motor function, track recovery progress, prevent injury, and personalize rehabilitation or training programs. Topics of interest include biomechanical assessments, motor control strategies, outcome-based rehabilitation protocols, and performance optimization through movement-focused interventions.

Submissions from kinesiology, physiotherapy, sports science, and related disciplines are encouraged. Both original research and systematic reviews that demonstrate the impact of movement-focused assessment and monitoring are invited.

Dr. Juri Taborri
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Journal of Functional Morphology and Kinesiology is an international peer-reviewed open access quarterly 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 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wearable sensors
  • motion analysis
  • sports performance
  • rehabilitation technology
  • biomechanics
  • injury prevention
  • remote monitoring
  • physiotherapy
  • human movement
  • kinesiology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

14 pages, 678 KB  
Article
Machine Learning-Based Prognostic Prediction for Knee Osteoarthritis After High Tibial Osteotomy Using Wavelet-Derived Gait Features
by Koji Iwasaki, Kento Sabashi, Hidenori Koyano, Yuji Kodama, Shigeyuki Sakurai, Kengo Ukishiro, Ryusuke Ito, Hisashi Matsumoto, Yuichiro Abe, Noriaki Mori, Chiharu Inoue, Yasumitsu Ohkoshi, Tomohiro Onodera, Eiji Kondo and Norimasa Iwasaki
J. Funct. Morphol. Kinesiol. 2026, 11(1), 94; https://doi.org/10.3390/jfmk11010094 - 26 Feb 2026
Viewed by 478
Abstract
Background: Osteotomy around the knee (OAK) is a joint-preserving surgery for knee osteoarthritis, yet some patients experience suboptimal outcomes. Preoperative identification of high-risk patients remains challenging. This study aimed to develop a machine learning model to predict clinical outcomes after OAK using [...] Read more.
Background: Osteotomy around the knee (OAK) is a joint-preserving surgery for knee osteoarthritis, yet some patients experience suboptimal outcomes. Preoperative identification of high-risk patients remains challenging. This study aimed to develop a machine learning model to predict clinical outcomes after OAK using preoperative gait acceleration data from inertial measurement units (IMUs). Methods: This multicenter prospective study enrolled patients undergoing OAK. Preoperative gait was recorded using synchronized IMUs placed on the lumbar spine and tibia. Lumbar and tibial signals were used for gait-cycle segmentation, while wavelet-based time–frequency features were extracted from tibial acceleration only. Outcomes were defined by achievement of the minimal clinically important difference in ≥3 KOOS subscales at 2-year follow-up (Good vs. Poor). Continuous wavelet transform features (5–20 Hz) were summarized as mean and standard deviation across six stance subphases. A Random Undersampling Boost classifier was trained and evaluated using nested leave-one-subject-out cross-validation. A sensitivity analysis using logistic regression confirmed that the IMU-based prediction score was independently associated with outcome after adjustment for baseline KOOS (p = 0.047). Results: Of 67 enrolled patients, 37 were classified as Good and 30 as Poor outcome. For machine learning analysis, 1173 tibial acceleration gait-cycle waveforms were usable. The model achieved an AUC of 0.744 (95% CI, 0.610–0.860) using a median of 15 features (range, 5–25) with sensitivity of 0.69 and specificity of 0.72. The most informative predictors were the mean magnitude in the 5–8 Hz band during loading response (0–17%) and variability in the 5–8 Hz band during late stance (67–83%). No significant differences in baseline demographics or radiographic parameters were found between outcome groups. Conclusions: Preoperative IMU-derived gait acceleration features showed moderate-to-good discrimination between outcome groups and may support preoperative risk stratification and individualized perioperative management. Full article
(This article belongs to the Special Issue Wearable Technology and Movement Analysis in Athletic Performance and Rehabilitation)
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12 pages, 1289 KB  
Article
Visual Search Behavior During Toileting in Older Patients During the Action-Planning Stage
by Lisa Sato, Naoto Noguchi, Munkhbayasgalan Byambadorj, Ken Kondo, Ryoto Akiyama and Bumsuk Lee
J. Funct. Morphol. Kinesiol. 2025, 10(4), 429; https://doi.org/10.3390/jfmk10040429 - 5 Nov 2025
Viewed by 900
Abstract
Background: Visual search supports action planning and target selection in daily life. Despite toileting being frequent yet high-risk in rehabilitation, gaze analyses specific to toileting remain limited. This study quantified visual search behavior during the approach phase of toileting. Methods: Twenty [...] Read more.
Background: Visual search supports action planning and target selection in daily life. Despite toileting being frequent yet high-risk in rehabilitation, gaze analyses specific to toileting remain limited. This study quantified visual search behavior during the approach phase of toileting. Methods: Twenty inpatients aged 65 years or older in a convalescent rehabilitation ward participated in the study. At the time of hospital admission, their gaze behavior from toilet room entry to arrival at the bowl was recorded using an eye tracker (Tobii Pro Glasses 2). Moreover, we evaluated a toilet-functional independence measure (toilet-FIM), comprising toileting, toilet transfer, and locomotion at discharge. Results: In multiple regression, a longer total gaze time directed towards the toilet seat was associated with a greater toilet-FIM independence (β = 0.446), whereas prolonged gaze to the toilet rim (β = −0.839) and to the right handrail (β = −0.621) were related to lower independence (adjusted R2 = 0.715). Conclusions: A toilet seat-oriented gaze implies effective action planning for safe sit-down, whereas toilet rim- or handrail-oriented gazes may reflect responses to visual salience or compensatory visual strategies related to reduced independence. These observations could improve our understanding of older patients’ motor planning and spatial perception in toileting. Full article
(This article belongs to the Special Issue Wearable Technology and Movement Analysis in Athletic Performance and Rehabilitation)
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