- LSF ID
- 57102
- ORCID
- 0000-0001-6415-0217
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
- GND
- 1015876811
- LSF ID
- 3881
- ORCID
- 0000-0001-9603-5272
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
Abstract:
Heart rate variability (HRV) is known to be correlated with emotional arousal, cognitive depletion, and health status. Despite the accurate HRV detection by various body-attached sensors, a contactless method is desirable for the HCI purposes. In this research, we propose a non-invasive contactless HRV measurement by Microsoft Kinect 2 sensor with Respiratory Sinus Arrhythmia (RSA) correction. The Infrared and RGB cameras are used to measure the heart rate signal, and its 3D Depth sensor is employed to capture the human respiratory signal to correct the initially calculated HRV with RSA. The correlation analysis among the calculated HRVs by different methods and devices showed a significant improvement in reliable HRV measurements. This study enlightens the researchers and developers to choose a proper method for HRV calculations based on their required accuracy and application.