The Impact of Control Interface on Features of Heart Rate Variability

Shared human-robot control for assistive machines can improve the independence of individuals with motor impairments. Monitoring elevated levels of workload can enable the assistive autonomy to adjust the control sharing in an assist-as-needed way, to achieve a balance between user fatigue, stress, and independent control. In this work, we aim to investigate how heart rate variability features can be utilized to monitor elevated levels of mental workload while operating a powered wheelchair, and how that utilization might vary under different control interfaces. To that end, we conduct a 22 person study with three commercial interfaces. Our results show that the validity and reliability of using the ultra-short-term heart-rate variability features as predictors of workload indeed are affected by the type of interface in use.