TY - GEN
T1 - Context-Aware control of smart objects via human-machine communication
AU - Muztoba, Md
AU - Qin, Eric
AU - Tran, Nicholas
AU - Ogras, Umit
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/4
Y1 - 2015/12/4
N2 - Brain-machine interface (BMI) is a promising technology that can provide accessibility to sensors and actuators using limited physical interaction. This technology can benefit millions of people with physical disabilities, such as Amyotrophic Lateral Sclerosis (ALS) and limb problems. However, its practical application depends critically on the accuracy of interpreting the commands received through BMI. This paper presents two techniques that exploit contextual awareness to improve the accuracy of communication using BMIs. We first present a technique that reduces the false interpretation probability significantly by analyzing the current system state. Then, we quantify the benefits of automating actions with the help of previously learned patterns. Experimental evaluations using a commercial BMI headset and a virtual reality environment show 2.6× decrease in the completion time of a navigation task.
AB - Brain-machine interface (BMI) is a promising technology that can provide accessibility to sensors and actuators using limited physical interaction. This technology can benefit millions of people with physical disabilities, such as Amyotrophic Lateral Sclerosis (ALS) and limb problems. However, its practical application depends critically on the accuracy of interpreting the commands received through BMI. This paper presents two techniques that exploit contextual awareness to improve the accuracy of communication using BMIs. We first present a technique that reduces the false interpretation probability significantly by analyzing the current system state. Then, we quantify the benefits of automating actions with the help of previously learned patterns. Experimental evaluations using a commercial BMI headset and a virtual reality environment show 2.6× decrease in the completion time of a navigation task.
UR - http://www.scopus.com/inward/record.url?scp=84962725538&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962725538&partnerID=8YFLogxK
U2 - 10.1109/BioCAS.2015.7348413
DO - 10.1109/BioCAS.2015.7348413
M3 - Conference contribution
AN - SCOPUS:84962725538
T3 - IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings
BT - IEEE Biomedical Circuits and Systems Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE Biomedical Circuits and Systems Conference, BioCAS 2015
Y2 - 22 October 2015 through 24 October 2015
ER -