This work presents a high‐performance, self‐powered triboelectric nanogenerator (TENG) embedded into an origami‐inspired fabric (“fabrigami”) structure for real‐time joint biomechanics monitoring. The device consists of electrospun polyvinylidene fluoride (PVDF) as the electronegative layer and silver‐doped cellulose acetate (Ag‐CA) as the electropositive layer, with enhanced surface charge density and mechanical durability. The fabrigami architecture amplifies contactseparation dynamics, enabling efficient detection of movements during joint motion while preserving conformability and air permeability. The optimized TENG based on 1.5% Ag in CA against PVDF exhibits remarkable electrical output characteristics, including an open‐circuit voltage of 155.9 V, short‐circuit current density of 8.134 mA m ⁻² , and transferred charge density of 65.62 µC m‐, with an instantaneous peak power density of 0.029 W m ⁻² achieved through an 11 MΩ external load resistance. The power conversion efficiency is 4.6–92.8% for 100–5 µm elastic compression of electrospun samples under 10 N, 2 Hz actuation. Sensor stability is observed over 15 000 cycles. The fabrigami knee sleeve includes a Bluetooth‐enabled microcontroller transmitting real‐time motion data wirelessly to measure joint angles and distinguish movement activities. This work demonstrates a novel strategy combining material innovation (Ag‐CA nanofibers) with structural configurability to create a breathable and power‐autonomous smart textile.

Objective. Training plays a significant role in motor imagery (MI), particularly in applications such as Motor Imagery-based Brain–Computer Interface (MIBCI) systems and rehabilitation systems. Previous studies have investigated the intricate relationship between cues and MI signals. However, the medium of presentation still remains an emerging area to be explored, as possible factors to enhance Motor Imagery signals. Approach. We hypothesize that the medium used for cue presentation can significantly influence both performance and training outcomes in MI tasks. To test this hypothesis, we designed and executed an experiment implementing no-feedback MI. Our investigation focused on three distinct cue presentation mediums—audio, screen, and virtual reality(VR) headsets—all of which have potential implications for BCI use in the Activities of Daily Lives. Main results. The results of our study uncovered notable variations in MI signals depending on the medium of cue presentation, where the analysis is based on 3 EEG channels. To substantiate our findings, we employed a comprehensive approach, utilizing various evaluation metrics including Event-Related Synchronization(ERS)/Desynchronization(ERD), Feature Extraction (using Recursive Feature Elimination (RFE)), Machine Learning methodologies (using Ensemble Learning), and participant Questionnaires. All the approaches signify that Motor Imagery signals are enhanced when presented in VR, followed by audio, and lastly screen. Applying a Machine Learning approach across all subjects, the mean cross-validation accuracy (Mean ± Std. Error) was 69.24 ± 3.12, 68.69 ± 3.3 and 66.1 ± 2.59 when for the VR, audio-based, and screen-based instructions respectively. Significance. This multi-faceted exploration provides evidence to inform MI-based BCI design and advocates the incorporation of different mediums into the design of MIBCI systems, experimental setups, and user studies. The influence of the medium used for cue presentation may be applied to develop more effective and inclusive MI applications in the realm of human–computer interaction and rehabilitation.

Long-term adherence to a Home Exercise Programme (HEP) is a difficult task for many athletes after an Anterior Cruciate Ligament Reconstruction (ACLR), making it difficult to go back to play sports. There are some common barriers that contribute to the tendency of patients not continuing with their HEP, like fear of re-injury, boredom, and lack of expectations. In my PhD research, I am using a user-centered approach to determine design guidelines for an immersive VR application for physical therapy, focused on ACL injuries. After identifying the needs of the users, cozy gaming characteristics have been chosen in order to design this application. Initial literature review and feedback has shown that a relaxing and task-oriented game could increase engagement on the prescribed exercises.