TY - GEN
T1 - A smartphone-based platform for portable, non-invasive, audio andvisual neurostimulation with a non-rhythmic sham stimulation mode
AU - Xing, Le
AU - Halpin, Stephen
AU - Casson, Alex
PY - 2023/10/9
Y1 - 2023/10/9
N2 - Non-invasive neuro stimulation is an emerging approach for chronic pain management, working by applying a flashing visual stimulation in the 10 Hz range, or via binaural beats were tones, differing by approximately 10 Hz, are played to each ear. Our previous work has presented smartphone based delivery of audio and visual stimulation, with smart phones being selected as a form factor which is portable, easy and convenient for people to use in home-settings, and readily integrated into body sensor network deployments. However, this did not include a sham stimulation mode allowing control studies to be performed. This paper presents a second generation Android smartphone App for providing non-invasive audio and visual stimulation. A sham mode is added via non-rhythmic neuro stimulation, jittering the instantaneous stimulation frequency. Hardware characterization and computational cost measurements demonstrate the high accuracy and efficiency of stimulation generation.
AB - Non-invasive neuro stimulation is an emerging approach for chronic pain management, working by applying a flashing visual stimulation in the 10 Hz range, or via binaural beats were tones, differing by approximately 10 Hz, are played to each ear. Our previous work has presented smartphone based delivery of audio and visual stimulation, with smart phones being selected as a form factor which is portable, easy and convenient for people to use in home-settings, and readily integrated into body sensor network deployments. However, this did not include a sham stimulation mode allowing control studies to be performed. This paper presents a second generation Android smartphone App for providing non-invasive audio and visual stimulation. A sham mode is added via non-rhythmic neuro stimulation, jittering the instantaneous stimulation frequency. Hardware characterization and computational cost measurements demonstrate the high accuracy and efficiency of stimulation generation.
U2 - 10.1109/bsn58485.2023.10331047
DO - 10.1109/bsn58485.2023.10331047
M3 - Conference contribution
BT - IEEE Body Sensor Networks conference
PB - IEEE
ER -