2026-10-06T04:23:24Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34013607 2026-10-02T14:10:02Z category_26278 category_26293 category_26299 portal_549 item_type_3 month_year_10_2026

Data for Comparison of Audio, Visual, and AudioVisual Biofeedback for Electromyographic Control Tanya Enoch (25122267) Prabhav Nadipi Reddy (10248845) Henry Lancashire (6784709) Biomedical instrumentation Rehabilitation engineering Biomedical engineering not elsewhere classified Biofeedback Electromyography EMG Sonification Visual Feedback Auditory Feedback <p dir="ltr">Audio biofeedback (AB) may present benefits over visual biofeedback (VB) in motor rehabilitation tasks expected to be combined with daily living. AB can be more discrete than VB and would not require looking at a display. This study aimed to investigate the use of AudioVisual Biofeedback (AVB), AB, and VB, for the control and precision of muscle contraction exercises.</p><p dir="ltr">15 adult participants were recruited to a study of biofeedback. Participants' forearm electromyography (EMG) was recorded using surface electrodes, amplified, filtered, and converted to binaural AB, screen-based VB, or combined co-incident AVB. The ability of participants to achieve and maintain root mean squared (RMS) EMG contraction and relaxation thresholds was assessed during contraction–relaxation cycle exercises.</p><p dir="ltr">The dataset comprises individual participant root mean squared (RMS) EMG recordings. Sampling rate is 40 Hz from RMS EMG features calculated online using 50-sample (50 ms) windows with 25 ms overlap. For each participant 8 recordings are provided:</p><ol><li>Contraction and relaxation cycles during visual biofeedback for muscle relaxation, ("P#<i>_</i>R_VB.csv"),</li><li>Contraction and relaxation cycles during audio biofeedback for muscle relaxation, ("P#<i>_</i>R_AB.csv"),</li><li>Contraction and relaxation cycles during audio+visual biofeedback for muscle relaxation, ("P#<i>_</i>R_AVB.csv"),</li><li>Contraction and relaxation cycles during visual biofeedback for muscle contraction, ("P#<i>_</i>C_VB.csv"),</li><li>Contraction and relaxation cycles during audio biofeedback for muscle contraction, ("P#<i>_</i>C_AB.csv"),</li><li>Contraction and relaxation cycles during audio+visual biofeedback for muscle contraction, ("P#<i>_</i>C_AVB.csv"),</li><li>Pre-trial threshold recording for muscle relaxation, ("P#_R_T.csv"),</li><li>Pre-trial threshold recording for muscle contraction, ("P#_C<i>_</i>T.csv").</li></ol><p dir="ltr">EMG recording was carried out using a Myoware Version 2 differential amplifier front end (Advancer Technologies) with 200× gain and 494.8 Hz low-pass filter. Additional signal conditioning was achieved with a 92 Hz second-order high-pass Sallen-Key filter, 10× gain second-stage amplifier, and mid-supply reference potential for ADC input range, all using MCP606 operational amplifiers (Microchip). Amplified and filtered EMG was sampled at 1 kHz using an Arduino Uno R3 microcontroller with a 10-bit ADC. Digitised raw EMG recordings were converted to RMS as described above. All data is supplied in raw ADC values in .csv column vectors, to convert to mV multiply by the conversion factor of 2.2195.</p><p dir="ltr">This participant study was approved by UCL Research Ethics Committee: 12363/005.</p> 2026-10-02T14:10:02Z Dataset Dataset 10.5522/04/34013607.v1 https://figshare.com/articles/dataset/Data_for_Comparison_of_Audio_Visual_and_AudioVisual_Biofeedback_for_Electromyographic_Control/34013607 CC BY 4.0