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Sensors in Neurophysiology and Neurorehabilitation (2nd Edition)
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Sensors in Neurophysiology and Neurorehabilitation (2nd Edition)

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

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 6404

Special Issue Editor

Prof. Dr. Andreia S. P. Sousa

E-Mail Website
Guest Editor
Department of Physiotherapy and Center for Rehabilitation Research (CIR), School of Health, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 400, 4200-072 Porto, Portugal
Interests: wearable biosensors; rehabilitation; human movement; postural control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

After a central nervous system injury, the presence of impairments that interfere with functional independence tasks is common. Therefore, motor control function recovery is the primary purpose of neurorehabilitation. However, despite several rehabilitation strategies having been adopted, a high percentage of patients do not reach functional independence.

The recovery of motor function after neural damage is difficult to predict. Patients with similar initial motor impairment may achieve widely disparate levels of motor function and independence. Being able to predict functional motor outcomes could help clinicians, patients, and families to set appropriate rehabilitation goals and make suitable plans for the level of support the patient is likely to need after discharge from hospital. However, making accurate predictions for individual patients based on clinical experience or on actual clinical assessment tools alone can be difficult.

This Special Issue aims to address all types of neurophysiology and neurorehabilitation sensors designed for motor control assessment and monitoring that could help the establishment of motor control dysfunction diagnosis and recovery prognosis and could also assist or guide the rehabilitation process in cases of central nervous system injury. Other conditions that lead to motor control impairment may also be considered.

This topic fits within the following scope of Sensors:

  • Smart/intelligent sensors;
  • Biosensors;
  • Wearable sensors, devices, and electronics;
  • MEMS/NEMS;
  • Remote sensors.

Prof. Dr. Andreia S. P. Sousa
Guest Editor

Manuscript Submission Information

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Related Special Issue

Published Papers (3 papers)

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Research

23 pages, 3703 KiB  
Article
An Analytical Approach for Naturalistic Cooperative and Competitive EEG-Hyperscanning Data: A Proof-of-Concept Study
by Gabriella Tamburro, Ricardo Bruña, Patrique Fiedler, Antonio De Fano, Khadijeh Raeisi, Mohammad Khazaei, Filippo Zappasodi and Silvia Comani
Sensors 2024, 24(10), 2995; https://doi.org/10.3390/s24102995 - 9 May 2024
Cited by 2 | Viewed by 1974
Abstract
Investigating the neural mechanisms underlying both cooperative and competitive joint actions may have a wide impact in many social contexts of human daily life. An effective pipeline of analysis for hyperscanning data recorded in a naturalistic context with a cooperative and competitive motor [...] Read more.
Investigating the neural mechanisms underlying both cooperative and competitive joint actions may have a wide impact in many social contexts of human daily life. An effective pipeline of analysis for hyperscanning data recorded in a naturalistic context with a cooperative and competitive motor task has been missing. We propose an analytical pipeline for this type of joint action data, which was validated on electroencephalographic (EEG) signals recorded in a proof-of-concept study on two dyads playing cooperative and competitive table tennis. Functional connectivity maps were reconstructed using the corrected imaginary part of the phase locking value (ciPLV), an algorithm suitable in case of EEG signals recorded during turn-based competitive joint actions. Hyperbrain, within-, and between-brain functional connectivity maps were calculated in three frequency bands (i.e., theta, alpha, and beta) relevant during complex motor task execution and were characterized with graph theoretical measures and a clustering approach. The results of the proof-of-concept study are in line with recent findings on the main features of the functional networks sustaining cooperation and competition, hence demonstrating that the proposed pipeline is promising tool for the analysis of joint action EEG data recorded during cooperation and competition using a turn-based motor task. Full article
(This article belongs to the Special Issue Sensors in Neurophysiology and Neurorehabilitation (2nd Edition))
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15 pages, 954 KiB  
Article
Assessing Gait & Balance in Adults with Mild Balance Impairment: G&B App Reliability and Validity
by Hina Shafi, Waqar Ahmed Awan, Sharon Olsen, Furqan Ahmed Siddiqi, Naureen Tassadaq, Usman Rashid and Imran Khan Niazi
Sensors 2023, 23(24), 9718; https://doi.org/10.3390/s23249718 - 8 Dec 2023
Cited by 3 | Viewed by 2225
Abstract
Smartphone applications (apps) that utilize embedded inertial sensors have the potential to provide valid and reliable estimations of different balance and gait parameters in older adults with mild balance impairment. This study aimed to assess the reliability, validity, and sensitivity of the Gait&Balance [...] Read more.
Smartphone applications (apps) that utilize embedded inertial sensors have the potential to provide valid and reliable estimations of different balance and gait parameters in older adults with mild balance impairment. This study aimed to assess the reliability, validity, and sensitivity of the Gait&Balance smartphone application (G&B App) for measuring gait and balance in a sample of middle- to older-aged adults with mild balance impairment in Pakistan. Community-dwelling adults over 50 years of age (N = 83, 50 female, range 50–75 years) with a Berg Balance Scale (BBS) score between 46/56 and 54/56 were included in the study. Data collection involved securing a smartphone to the participant’s lumbosacral spine. Participants performed six standardized balance tasks, including four quiet stance tasks and two gait tasks (walking looking straight ahead and walking with head turns). The G&B App collected accelerometry data during these tasks, and the tasks were repeated twice to assess test-retest reliability. The tasks in quiet stance were also recorded with a force plate, a gold-standard technology for measuring postural sway. Additionally, participants completed three clinical measures, the BBS, the Functional Reach Test (FRT), and the Timed Up and Go Test (TUG). Test-retest reliability within the same session was determined using intraclass correlation coefficients (ICCs) and the standard error of measurement (SEM). Validity was evaluated by correlating the G&B App outcomes against both the force plate data and the clinical measures using Pearson’s product-moment correlation coefficients. To assess the G&B App’s sensitivity to differences in balance across tasks and repetitions, one-way repeated measures analyses of variance (ANOVAs) were conducted. During quiet stance, the app demonstrated moderate reliability for steadiness on firm (ICC = 0.72) and compliant surfaces (ICC = 0.75) with eyes closed. For gait tasks, the G&B App indicated moderate to excellent reliability when walking looking straight ahead for gait symmetry (ICC = 0.65), walking speed (ICC = 0.93), step length (ICC = 0.94), and step time (ICC = 0.84). The TUG correlated with app measures under both gait conditions for walking speed (r −0.70 and 0.67), step length (r −0.56 and −0.58), and step time (r 0.58 and 0.50). The BBS correlated with app measures of walking speed under both gait conditions (r 0.55 and 0.51) and step length when walking with head turns (r = 0.53). Force plate measures of total distance wandered showed adequate to excellent correlations with G&B App measures of steadiness. Notably, G&B App measures of walking speed, gait symmetry, step length, and step time, were sensitive to detecting differences in performance between standard walking and the more difficult task of walking with head turns. This study demonstrates the G&B App’s potential as a reliable and valid tool for assessing some gait and balance parameters in middle-to-older age adults, with promise for application in low-income countries like Pakistan. The app’s accessibility and accuracy could enhance healthcare services and support preventive measures related to fall risk. Full article
(This article belongs to the Special Issue Sensors in Neurophysiology and Neurorehabilitation (2nd Edition))
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6 pages, 654 KiB  
Communication
Long-Term Electrode–Skin Impedance Variation for Electromyographic Measurements
by Andreia S. P. Sousa, Andreia Noites, Rui Vilarinho and Rubim Santos
Sensors 2023, 23(20), 8582; https://doi.org/10.3390/s23208582 - 19 Oct 2023
Cited by 2 | Viewed by 1700
Abstract
This study aims to observe the evolution of the electrode–skin interface impedance of surface EMG electrodes over the time taken to determine the time of stabilization. Eight healthy subjects participated in the study. Electrode–skin impedance was evaluated in the rectus abdominal muscle every [...] Read more.
This study aims to observe the evolution of the electrode–skin interface impedance of surface EMG electrodes over the time taken to determine the time of stabilization. Eight healthy subjects participated in the study. Electrode–skin impedance was evaluated in the rectus abdominal muscle every five minutes, over a total period of 50 min. A reduction of 13.23% in the impedance values was observed in minute 10 (p = 0.007), and a reduction of 9.02% was observed in minute 15 (p = 0.029). No statistically significant differences were observed in the other instants evaluated. The findings obtained in the present study demonstrate a decrease in electrode–skin impedance from minute 5 to minute 15, followed by a stabilization period with a low percentage of variation till minute 50. Full article
(This article belongs to the Special Issue Sensors in Neurophysiology and Neurorehabilitation (2nd Edition))
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