“Physiological Parameters Measurement Based on Wheelchair Embedded Sensors and Advanced Signal Processing”
Submitted by: Hira Naqvi (2k8-ee-214) Roshaan Khan (2k8-ee-235) Usman Asif Khan (2k8-ee-253)
Physiological Parameters Measurement
Based on Wheelchair Embedded Sensors and
Advanced Signal Processing
Introduction:- This paper presents a multisensing system with wireless communication capabilities embedded on a smart wheelchair that can measure physiological parameters such as heart rate and respiratory rate in an unobtrusive way. Ballistocardiography (BCG) sensors and a three-axis inertial microelectromechanical system accelerometer are embedded on the seat or in the backrest of the wheelchair and the acquired data are transmitted by Wi-Fi to a laptop computer for advanced data processing and logging. In addition, a 3-D accelerometer with ZigBee communication capability is used to extract information about the user’s posture. Considering the static and dynamic use of the wheelchair, an extended set of measurements for different utilization scenarios was analyzed. An important part of this paper is focused on BCG noise and artifacts removal and heart rate and respiratory rate accurate estimation from BCG signal using wavelet-based filtering and independent component analysis algorithms. A study on wavelet-based filtering considering different types of mother wavelets and different levels of decomposition was also carried out. In the future, other signals will also be acquired to improve the system capabilities and flexibility.
Unobtrusive Measures:-
Unobtrusive measures are measures that don't require the researcher to intrude in the research context. Direct and participant observation requires that the researcher be physically present. This can lead the respondents to alter their behavior in order to look good in the eyes of the researcher. A questionnaire is an interruption in the natural stream of behavior. Respondents can get tired of filling out a survey or resentful of the
Physiological Parameters Measurement
Based on Wheelchair Embedded Sensors and
Advanced Signal Processing
Introduction:- This paper presents a multisensing system with wireless communication capabilities embedded on a smart wheelchair that can measure physiological parameters such as heart rate and respiratory rate in an unobtrusive way. Ballistocardiography (BCG) sensors and a three-axis inertial microelectromechanical system accelerometer are embedded on the seat or in the backrest of the wheelchair and the acquired data are transmitted by Wi-Fi to a laptop computer for advanced data processing and logging. In addition, a 3-D accelerometer with ZigBee communication capability is used to extract information about the user’s posture. Considering the static and dynamic use of the wheelchair, an extended set of measurements for different utilization scenarios was analyzed. An important part of this paper is focused on BCG noise and artifacts removal and heart rate and respiratory rate accurate estimation from BCG signal using wavelet-based filtering and independent component analysis algorithms. A study on wavelet-based filtering considering different types of mother wavelets and different levels of decomposition was also carried out. In the future, other signals will also be acquired to improve the system capabilities and flexibility.
Unobtrusive Measures:-
Unobtrusive measures are measures that don't require the researcher to intrude in the research context. Direct and participant observation requires that the researcher be physically present. This can lead the respondents to alter their behavior in order to look good in the eyes of the researcher. A questionnaire is an interruption in the natural stream of behavior. Respondents can get tired of filling out a survey or resentful of the