In the area of biomedical signal monitoring, wearable electronics represents a dynamically growing field with a significant impact on the market of commercial products of biomedical signal monitoring and acquisition, as well as consumer electronic for vital functions monitoring. Since the electrodes are perceived as one of the most important part of the biomedical signal monitoring, they have been one of the most frequent subjects in the research community. Electronic textile (e-textile), also called smart textile represents a modern trend in the wearable electronics, integrating of functional materials with common clothing with the goal to realize the devices, which include sensors, antennas, energy harvesters and advanced textiles for self-cooling and heating. The area of textile electrodes and e-textile is perceived as a multidisciplinary field, integrating material engineering, chemistry, and biomedical engineering. In this review, we provide a comprehensive view on this area. This multidisciplinary review integrates the e-textile characteristics, materials and manufacturing of the textile electrodes, noise influence on the e-textiles performance, and mainly applications of the textile electrodes for biomedical signal monitoring and acquisition, including pressure sensors, electrocardiography, electromyography, electroencephalography and electrooculography monitoring.

Background and Objectives: The consequences of stroke have a significant impact on self-sufficiency and health-related quality of life (HRQoL). Virtual reality (VR)-based rehabilitation has the potential to impact these modalities, but information on timing, volume, and intensity is not yet available. The aim of this randomized controlled trial (1:1) was to evaluate the impact of conventional rehabilitation combined with VR on self-care and domains of HRQoL in patients ≤6 months post-stroke. Materials and Methods: The intervention group completed a total of 270 min of conventional VR + rehabilitation sessions. The control group underwent conventional rehabilitation only. Primary assessments with the WHO disability assessment schedule 2.0 (WHODAS 2) questionnaire were conducted before rehabilitation (T0), after completion of the intervention (T1), and at the 4-week follow-up (T2); secondary outcomes included self-sufficiency and balance assessments. Results: Fifty patients completed the study (mean age 61.2 ± 9.0 years, time since stroke 114.3 ± 39.4 days). There were no statistically significant differences between the groups in WHODAS 2, self-sufficiency, and balance scores (p > 0.05). Conclusions: In the experimental group, there was a statistically significant difference in WHODAS 2, assessment of self-sufficiency, and balance scores before and after therapy (p < 0.05). VR appears to be a suitable tool to supplement and modify rehabilitation in patients after stroke.