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Advanced Sensors for Neurorehabilitation: Empowering Precision and Personalized Therapy—2nd Edition
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Advanced Sensors for Neurorehabilitation: Empowering Precision and Personalized Therapy—2nd Edition

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

Deadline for manuscript submissions: 15 December 2025 | Viewed by 1048

Special Issue Editor

Dr. Vance Bergeron

E-Mail Website
Guest Editor
Centre National de la Recherche Scientifique (CNRS), Ecole Normale Supérieure de Lyon (ENSL), Lyon, France
Interests: neurorehabilitation; human–machine interfaces; functional electrical stimulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurorehabilitation aims to restore and enhance motor and cognitive functions in individuals with neurological disorders. Here, we wish to delve into the advances, challenges, and future prospects of advanced sensor technologies in neurorehabilitation. Recent achievements in sensor technology have revolutionized the field, offering objective assessments and personalized interventions. This Special Issue provides an overview of advanced sensors for neurorehabilitation and their potential to transform traditional approaches.

Advanced sensors, such as wearables, robots, and neuroimaging technologies, enable the real-time monitoring of physiological and biomechanical parameters. They quantify motor performance, assess neuromuscular activation, and evaluate brain activity, providing insights into intervention effectiveness. High-resolution data collected by these sensors can be analyzed using artificial intelligence and machine learning algorithms to enhance our understanding of neuroplastic processes.

By enabling personalized treatment plans, advanced sensors optimize neurorehabilitation and improve functional outcomes. Clinicians benefit from objective measures, allowing for the precise monitoring of progress and data-driven adjustments to therapy. Patients receive immediate feedback, enhancing engagement and motivation during rehabilitation.

In conclusion, advanced sensors in neurorehabilitation hold promise for transforming the field. Objective assessments, personalized interventions, and real-time feedback have the potential to revolutionize traditional rehabilitation, leading to improved patient outcomes and enhanced quality of life.

Dr. Vance Bergeron
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. 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

  • neurorehabilitation
  • advanced sensors
  • neural interfaces
  • rehabilitation technology
  • wearable sensors
  • human–machine interface

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Related Special Issue

Published Papers (2 papers)

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Research

21 pages, 2205 KB  
Article
Combined Individual Experience and Accelerometry Measurement of Upper Limb Use in Daily Activities in Real Time After Stroke
by Isuru Senadheera, Prasad Hettiarachchi, Brendon Haslam, Rashmika Nawaratne, Michael Pollack, Susan Hillier, Michael Nilsson, Damminda Alahakoon and Leeanne M Carey
Sensors 2025, 25(23), 7330; https://doi.org/10.3390/s25237330 (registering DOI) - 2 Dec 2025
Viewed by 149
Abstract
Use of the upper limb to engage in everyday activities is a key indicator of functional recovery of stroke survivors. In addition to functional capacity, personal and environmental factors contribute to real-world upper limb use post-stroke. We aimed to combine data from the [...] Read more.
Use of the upper limb to engage in everyday activities is a key indicator of functional recovery of stroke survivors. In addition to functional capacity, personal and environmental factors contribute to real-world upper limb use post-stroke. We aimed to combine data from the experience sampling method (ESM), a method used to capture real-time engagement in daily activities, with accelerometry, an objective measurement of arm use, to evaluate arm use behaviours of adult stroke survivors living in real-world environments. Thirty mild–moderately impaired stroke survivors and 30 age-standardized healthy individuals were monitored over 7 days, using accelerometers on both wrists and four ESM beeps per day to capture individual experiences in daily activities. Stroke survivors showed significantly lower use of the affected arm across all activity domains compared to the non-dominant arm of healthy participants and reported perceived lower skill and higher challenge levels. Physical context, motor capabilities and activity type were associated with affected arm use behaviour, with greater use observed during social settings and in physically demanding tasks. These findings demonstrate that combining ESM with accelerometry provides a novel, ecologically valid framework to capture and interpret the interplay between capacity, context, and behaviour in everyday life. This approach offers opportunities to design personalized, context-aware rehabilitation strategies that promote meaningful functional reintegration after stroke. Full article
(This article belongs to the Special Issue Advanced Sensors for Neurorehabilitation: Empowering Precision and Personalized Therapy—2nd Edition)
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17 pages, 3765 KB  
Article
Use of Accelerometers to Monitor Motor Activity During HABIT-ILE for Chronic Stroke: An Exploratory Study
by Merlin Somville, Zélie Rosselli, Edouard Ducoffre, Massimo Penta, Tristan Smeesters, Yannick Bleyenheuft and Geoffroy Saussez
Sensors 2025, 25(21), 6656; https://doi.org/10.3390/s25216656 - 31 Oct 2025
Viewed by 661
Abstract
(1) Background: Hand and Arm Bimanual Intensive Therapy Including Lower Extremities (HABIT-ILE) is a high-dose evidence-based neurorehabilitation. This study aims to develop and validate a protocol using three inertial measurement units (IMUs) to objectively document upper and lower extremities’ (UE; LE) motor activity [...] Read more.
(1) Background: Hand and Arm Bimanual Intensive Therapy Including Lower Extremities (HABIT-ILE) is a high-dose evidence-based neurorehabilitation. This study aims to develop and validate a protocol using three inertial measurement units (IMUs) to objectively document upper and lower extremities’ (UE; LE) motor activity during a HABIT-ILE intervention in chronic stroke adults. (2) Method: Thirteen adults (57.1 y ± 11.3) who completed 65 h of HABIT-ILE (2 weeks, 6.5 h/d) were included. Daily motor activity was recorded with IMUs placed on both wrists and one thigh with nine IMU-derived variables extracted to evaluate motor activity and posture. Each variable was correlated with baseline abilities and day-to-day patterns were observed with subgroup analyses based on baseline dexterity and walking endurance. Day-to-day patterns were highlighted based on mean values and effect size analyses. (3) Results: Only the Magnitude and Use ratios showed high correlations with baseline abilities, with a day-to-day specific pattern highlighted for participants with moderate to good dexterity at baseline. (4) Conclusions: All participants reported a high level of engagement during HABIT-ILE independently of their baseline abilities. Although we could not detect a global trend to document the content of a HABIT-ILE intervention, these exploratory results suggest IMU monitoring to be relevant to characterize therapeutic content. Full article
(This article belongs to the Special Issue Advanced Sensors for Neurorehabilitation: Empowering Precision and Personalized Therapy—2nd Edition)
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