Inertial Sensors and Muscle Electrical Signals in Human-Computer Interaction

2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA 2017) 2018
Armands Ancāns, Artis Rozentāls, Krišjānis Nesenbergs, Modris Greitāns

Assistive technology, such as interactive computer applications, has a major role in providing independence to many individuals, but computer interaction using traditional input devices can be challenging for people with disabilities. In this study, a bimodal computer control device is proposed uniting muscle electrical signals and inertial sensor data to provide efficient manual target selection in addition to existing inertial sensor-based solutions for head position tracking and computer cursor control. An embedded system consisting of 9-axis inertial measurement unit and electromyography sensors was proposed and a wireless headband prototype was developed in order to measure system performance and compare it with similar studies. Results show that manual target selection using facial muscle electrical signals instead of automatic dwell time increases the speed of human-computer interaction.

Atslēgas vārdi
assisted living;electromyography;human computer interaction;medical signal processing;muscle;sensors;user interfaces;9-axis inertial measurement unit;assistive technology;bimodal computer control device;computer cursor control;electromyography sensors;embedded system;facial muscle electrical signals;head position tracking;human-computer interaction;inertial sensor data;manual target selection;muscle electrical signals;traditional input devices;wireless headband prototype;Accelerometers;Electrodes;Electromyography;Human computer interaction;Muscles;Prototypes;Sensors;accelerometer;assistive technology;electromyography (EMG);head mouse;human computer interaction (HCI);inertial sensors (IMU);wearable
DOI
10.1109/ICTA.2017.8336064
Hipersaite
https://ieeexplore.ieee.org/document/8336064

Ancāns, A., Rozentāls, A., Nesenbergs, K., Greitāns, M. Inertial Sensors and Muscle Electrical Signals in Human-Computer Interaction. No: 2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA 2017), Omāna, Maskata, 19.-21. decembris, 2017. IEEE: Piscataway, 2018, 1.-6.lpp. e-ISSN 2379-4402. Pieejams: doi:10.1109/ICTA.2017.8336064

Publikācijas valoda
English (en)