An unobtrusive biomedical system embedded on a wheelchair successfully measured heart rate and respiratory rate using BCG and accelerometer sensors with wavelet-based filtering and ICA algorithms.
A wheelchair-embedded monitoring system using ballistocardiography and accelerometry can unobtrusively estimate heart rate and respiratory rate despite motion artifacts.
A biomedical system embedded on a wheelchair able to measure heart rate, respiratory rate, and the wheelchair motion state is presented. A wireless multi-channel acquisition module is connected to a BCG (ballistocardiography) unit and to an inertial 3-axial MEMS accelerometer based unit. The sensing units are embedded on the seat and backrest of the wheelchair and the acquired data is transmitted through Wi-Fi connection to a remote processing unit expressed by a laptop PC. Considering the different motion situations of the wheelchair when utilized by the user, an important part of the work was focused on BCG noise and artifacts removal as well as to heart rate and respiratory rate accurate estimation from BCG signal using wavelet based filtering and ICA (Independent Component Analysis) algorithms. Experimental results for different scenarios of wheelchair utilization are included in the paper.
Postolache et al. (Fri,) reported a other. Unobtrusive heart rate and respiratory rate monitor embedded on a wheelchair was evaluated on Heart rate and respiratory rate accurate estimation from BCG signal. An unobtrusive biomedical system embedded on a wheelchair successfully measured heart rate and respiratory rate using BCG and accelerometer sensors with wavelet-based filtering and ICA algorithms.