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Sensor-Based Rehabilitation in Neurological Diseases

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (28 February 2026) | Viewed by 5096

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Special Issue Editors

Dr. Andrea Tacchino

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Guest Editor

Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
Interests: neurorehabilitation

Dr. Jessica Podda

E-Mail Website
Guest Editor

Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
Interests: neurorehabilitation; validation of novel technological devices for assessment and rehabilitation in multiple sclerosis; cognitive phenotyping

Special Issue Information

Dear Colleagues,

This Special Issue, "Sensor-Based Rehabilitation in Neurological Diseases", aligns with the scope of Sensors by focusing on the development and application of sensor technologies to enhance rehabilitation outcomes in individuals with neurological disorders. The integration of wearable sensors, robotic-assisted devices, virtual reality, and artificial intelligence has revolutionized the field, enabling objective, real-time monitoring and personalized therapeutic interventions. By bridging engineering and clinical research, sensor-based approaches contribute to the advancement of precision rehabilitation, improving patient care and functional recovery. This Special Issue welcomes original research and review articles on novel sensing technologies, data analysis techniques, and clinical applications for motor, cognitive, and sensory functions in individuals with neurological disorders. Contributions addressing challenges, future directions, and the translation of these innovations into clinical practice are also encouraged.

Dr. Andrea Tacchino
Dr. Jessica Podda
Guest Editors

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Keywords

sensor-based rehabilitation
neurological disorders
wearable sensors
motor and cognitive rehabilitation
artificial intelligence in rehabilitation
virtual reality therapy
robotic-assisted rehabilitation
digital biomarkers
personalized rehabilitation
telerehabilitation

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Published Papers (5 papers)

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Research

17 pages, 1898 KB

Open AccessArticle

Side-Dependent Trunk Muscle Modulation During Sit-to-Stand After Stroke: An Exploratory EMG and Kinematic Study

by Grazia Cravero, Alice De Luca, Beatrice Lagomarsino, Carmelo Lentino, Giorgia Marchesi, Debora Siri, Camilla Pierella and Maura Casadio

Sensors 2026, 26(8), 2353; https://doi.org/10.3390/s26082353 - 10 Apr 2026

Viewed by 518

Abstract

Sit-to-stand (STS) is a fundamental functional task frequently impaired after stroke and widely used in rehabilitation to assess motor control and balance. While lower-limb kinematic and muscular asymmetries during STS have been documented, the contribution of trunk muscle coordination to compensatory strategies has received limited attention. We investigated STS performance in seven individuals with chronic right-sided hemiparesis under two conditions (free arms and crossed arms) to characterize phase-dependent kinematic asymmetries and side-dependent trunk muscle modulation relevant to rehabilitation practice. Optoelectronic motion capture was synchronized with bilateral surface electromyography, providing time-aligned kinematic and neuromuscular signals for sensor-based assessment of STS. Participants exhibited prolonged and highly variable STS durations, along with ankle asymmetries during the rising and lowering phases and hip asymmetries during upright standing, indicating increased reliance on the less impaired limb. Electromyography revealed side-dependent modulation of trunk muscles, notably latissimus dorsi, erector spinae longissimus, and multifidus, characterized by a prolonged relative contribution on the more impaired side. These findings suggest that altered trunk muscle modulation contributes to compensatory STS strategies after stroke and highlight the importance of trunk-focused neuromuscular assessment to guide individualized rehabilitation interventions aimed at improving symmetry, postural stability, and movement efficiency. Full article

(This article belongs to the Special Issue Sensor-Based Rehabilitation in Neurological Diseases)

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11 pages, 383 KB

Open AccessArticle

Manual Dexterity Shows Greater Discretionary Value than Sensor-Based Gait and Balance Measures in Identifying Early Functional Impairment in Multiple Sclerosis

by Mousa Hujirat and Alon Kalron

Sensors 2026, 26(6), 1866; https://doi.org/10.3390/s26061866 - 16 Mar 2026

Viewed by 486

Abstract

Objective: To determine which physical clinical test best differentiates minimally impaired people with MS (pwMS) from healthy controls and to compare the discriminatory value of upper limb clinical assessments with sensor-based gait and postural control measures. Methods: Forty-one participants (21 pwMS, 20 matched healthy controls) completed a single testing session including upper limb clinical assessments (Nine-Hole Peg Test [9HPT], grip strength), gait (Timed 25-Foot Walk, Six-Minute Walk Test, and cognitive–walking dual task), and static balance assessments using wearable inertial sensors (APDM Mobility Lab system). Dual-task costs (DTCs) were calculated for gait parameters. Between-group comparisons were performed using independent t-tests. Pearson correlation analyses were conducted to examine interrelationships among gait variables, and a parsimonious binary logistic regression model was constructed, including non-dominant 9HPT and dual-task walking speed. Receiver operating characteristic (ROC) analyses were performed to evaluate discriminative performance and determine the optimal 9HPT cutoff. Results: PwMS performed significantly slower on the 9HPT for both hands (p ≤ 0.006) and demonstrated reduced walking performance and higher gait DTCs (p ≤ 0.041) compared with controls. No significant group differences were observed in grip strength or sensor-based postural control. In multivariable analysis, the overall model was significant (p < 0.001; Nagelkerke R² = 0.49), and the non-dominant 9HPT remained the only independent predictor of group status (OR = 1.75, 95% CI [1.17–2.61]), whereas dual-task walking speed was not significant after adjustment. ROC analysis demonstrated good discriminative ability for the non-dominant 9HPT (AUC = 0.84, 95% CI [0.71–0.97]) and acceptable discrimination for dual-task walking speed (AUC = 0.75, 95% CI [0.60–0.90]). The optimal 9HPT cutoff was ≥21.4 s, yielding 71% sensitivity and 100% specificity in this cohort. Conclusions: Manual dexterity of the non-dominant hand may serve as a sensitive screening marker of early functional impairment in MS, demonstrating greater discriminatory value than sensor-based gait and balance measures. These findings support the inclusion of upper limb dexterity testing in the routine assessment of minimally impaired pwMS. Validation in larger, longitudinal cohorts is warranted. Full article

(This article belongs to the Special Issue Sensor-Based Rehabilitation in Neurological Diseases)

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21 pages, 1566 KB

Open AccessArticle

by Elisa Misley, Maria Chiara Delatto, Maura Casadio, Tommaso Falchi Delitala, Valeria Falzarano and Giorgia Marchesi

Sensors 2026, 26(6), 1847; https://doi.org/10.3390/s26061847 - 15 Mar 2026

Viewed by 567

Abstract

Age-related declines in balance and cognitive function increase fall risk and reduce quality of life in older adults and people with neurological disorders. Studying these changes in unimpaired adults provides a normative reference for identifying pathological deviations. However, most dual-task studies focus on single cognitive tasks and static conditions, specifically during gait, limiting understanding of how cognitive demand interacts with postural control while standing and during dynamic challenges. This study identified cognitive and motor outcomes most sensitive to age-related differences during motor–cognitive dual tasks of varying complexity across static and dynamic balance conditions, accounting for minimal detectable change. Sixty healthy adults performed dual-tasks ranging from simple motor activities to complex cognitive challenges (Stroop Test) while standing on a robotic platform. Cognitive performance (reaction time) and balance outcomes, including trunk and center of pressure (CoP) sway area, were assessed. Reaction time was sensitive to aging, with standardized estimates ranging from 0.014 to 0.036. The highest values occurred in the most demanding dual-task condition, enabling detection of meaningful change over short timeframes. Age effects on balance were modest under static conditions but amplified during dynamic perturbations across all dual tasks. In the SCWT 3 condition, standardized estimates for CoP sway area increased from 0.006 in the static condition to 0.047 in the passive condition, reflecting an approximately eightfold increase in age sensitivity. Trunk sway primarily reflected cognitive load, whereas CoP sway was most sensitive to balance perturbations and exceeded minimal detectable thresholds over only a couple of years. These findings support sensitive task–condition combinations for early detection and monitoring of age-related cognitive and balance decline. Full article

(This article belongs to the Special Issue Sensor-Based Rehabilitation in Neurological Diseases)

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12 pages, 640 KB

Open AccessArticle

Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and Ergonomic Assessment

by Hande Argunsah, Begum Yalcin, Mehmet Alper Ergin, Gokay Coruhlu, Mustafa Yalcin, Volkan Patoglu and Zeynep Guven

Sensors 2026, 26(1), 88; https://doi.org/10.3390/s26010088 - 23 Dec 2025

Cited by 2 | Viewed by 823

Abstract

Effective upper-extremity rehabilitation requires intensive and precise movement training, yet conventional therapies lack accurate motion tracking. Robotic exoskeletons address this limitation but are often hindered by ergonomic misalignment and limited adaptability. The AssistOn-Arm, a novel self-aligning exoskeleton, integrates ergonomic design and back-drivable actuation to enhance comfort and facilitate natural user interaction. This study aimed to assess the usability and ergonomics of the device in healthy participants and to conduct a pilot clinical evaluation in individuals with upper-extremity impairments. Thirty healthy participants and twelve patients with shoulder impairments performed predefined tasks under participant-active and device-active conditions. Kinematic data captured concurrently with AssistOn-Arm and Xsens MVN demonstrated strong agreement between conditions. Quantitative analysis revealed no significant differences (p > 0.05) in flexion, elevation, abduction–adduction, and external rotation, indicating reliable alignment with natural joint axes. Significant differences (p < 0.05) were observed only in sagittal hyperextension and internal rotation, reflecting device mechanical constraints. The study confirms the clinical feasibility of AssistOn-Arm as a sensor-driven, self-aligning exoskeleton that bridges engineering innovation and precision rehabilitation, paving the way for its integration into clinical practice. Full article

(This article belongs to the Special Issue Sensor-Based Rehabilitation in Neurological Diseases)

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17 pages, 2767 KB

Open AccessArticle

A Novel Whole-Body Wearable Technology for Motor Assessment in Multiple Sclerosis: Feasibility and Usability Pilot Study

by Jessica Podda, Erica Grange, Claudia Latella, Andrea Tacchino, Enrico Valli, Ludovica Danovaro, Gianluca Milani, Marco Forleo, Antonella Tatarelli, Davide Gorbani, Alex Coppola, Ludovico Pedullà, Giampaolo Brichetto and Daniele Pucci

Sensors 2025, 25(19), 6214; https://doi.org/10.3390/s25196214 - 7 Oct 2025

Viewed by 1859

Abstract

(1) Background: Technological advancements provide new opportunities to objectively assess motor deficits in people with Multiple Sclerosis (PwMS). This pilot study aimed to evaluate the performance and usability of iFeel, a novel wearable system which integrates inertial sensors, instrumented shoes, and an AI-based algorithm. (2) Methods: Sixteen adult PwMS (Expanded Disability Status Scale—EDSS ≤ 6) performed motor tests (Timed 25-Foot Walk—T25FW; Timed Up and Go—TUG) both with and without the iFeel suit. Patient-reported outcomes (PROs) were also collected to assess perceived fatigue, dual-task impact, and walking difficulties. System Usability Scale (SUS) and ad hoc questionnaires have been further administered to test usability. (3) Results: No significant differences were found between the clinician and system-based scores for both T25FW (p = 0.383) and TUG (p = 0.447). Reliability analyses showed good agreement for T25FW (Intraclass Correlation Coefficient—ICC = 0.83) and excellent agreement for TUG (ICC = 0.92). Sensor-derived measures correlated strongly with PROs on fatigue, dual-task interference, and mobility. Usability was rated high (SUS: 78.6 ± 16.1), with participants reporting minimal discomfort and positive perceptions of iFeel usefulness for rehabilitation, health monitoring, and daily activities. (4) Conclusions: This pilot study provides preliminary yet promising evidence on the feasibility, usability, and perceived usefulness of the iFeel technology for motor assessment in PwMS. The findings support its further development and potential integration into clinical practice, particularly for remote or continuous motor monitoring. Full article

(This article belongs to the Special Issue Sensor-Based Rehabilitation in Neurological Diseases)

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