sensors-logo

Journal Browser

Journal Browser

Sensors for Human Movement Recognition and Analysis: 2nd Edition

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

Deadline for manuscript submissions: 25 May 2026 | Viewed by 723

Special Issue Editor


E-Mail Website
Guest Editor
Faculty of Science and Engineering, Curtin University, Perth 6845, Australia
Interests: assistive technology; vision impairment; embedded system; steaching and learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce the second edition of this Special Issue of Sensors and to invite you to submit a manuscript. The original Special Issue can be accessed at https://www.mdpi.com/journal/sensors/special_issues/Y82VW94F7P. Recently, there has been an increase in the number of consumer-level smart sensors and wearables designed for movement monitoring. However, there is often a lack of academic research and validation on the methods used by these devices. This Special Issue aims to compile original research and review articles on recent advances in sensors for human movement recognition and analysis. Potential applications include, but are not limited to, the following:

  • Assistive technology;
  • Rehabilitation;
  • Sport Science;
  • Smart PPE equipment.

Please note that, in accordance with MDPI Sensors’ scope, full experimental details must be provided so that the results can be reproduced. Additionally, manuscripts containing data from human participants must obtain ethics approval from the relevant authorizing bodies. Cross-disciplinary research collaborations between engineers and health science clinicians or researchers are of particular interest, as these collaborations can provide valuable feedback on the clinical validity of the measurements. 

Prof. Dr. Iain D. Murray
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 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.

Keywords

  • assistive technology
  • rehabilitation
  • sport science
  • smart PPE equipment
  • wearables
  • human movement recognition

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

13 pages, 1987 KB  
Article
Evaluation of Commercial Camera-Based Solutions for Tracking Hand Kinematics
by Alexander H. Sprague, Christopher Vogel, Mylah Williams, Evelynne Wolf and Derek Kamper
Sensors 2025, 25(18), 5716; https://doi.org/10.3390/s25185716 - 13 Sep 2025
Viewed by 464
Abstract
Tracking hand kinematics is essential for numerous clinical and scientific applications. Markerless motion capture devices have advantages over other modalities in terms of calibration, set up, and overall ease of use; however, their accuracy during dynamic tasks has not been fully explored. This [...] Read more.
Tracking hand kinematics is essential for numerous clinical and scientific applications. Markerless motion capture devices have advantages over other modalities in terms of calibration, set up, and overall ease of use; however, their accuracy during dynamic tasks has not been fully explored. This study examined the performance of two popular markerless systems, the Leap Motion Controller 2 (LM2) and MediaPipe (MP), in capturing joint motion of the digits. Data were compared to joint motion collected from a marker-based multi-camera system (Vicon). Eleven participants performed six tasks with their dominant right hand at three movement speeds while all three devices simultaneously captured the position of hand landmarks. Using these data, digit joint angles were calculated. The root mean squared error (RMSE) and correlation coefficient (r) relative to the Vicon angles were computed for LM2 and MP. LM2 achieved a lower error (p < 0.001, mean RMSE = 14.8°) and a higher correlation (p = 0.007, mean r = 0.58) than the MP system (mean RMSE = 22.5°, mean r = 0.45). Greater movement speed led to significantly higher RMSE (p < 0.001) and lower r (p < 0.001) for MP but not for LM2. Error was substantially greater for the proximal interphalangeal joint than for other finger joints, although r values were higher for this joint. Overall, the LM2 and MP systems were able to capture motion at the joint level across digits for a variety of tasks in real time, although the level of error may not be acceptable for certain applications. Full article
(This article belongs to the Special Issue Sensors for Human Movement Recognition and Analysis: 2nd Edition)
Show Figures

Figure 1

Back to TopTop