Heartbeat detection from a hydraulic bed sensor using a clustering approach

Abstract

Encouraged by previous performance of a hydraulic bed sensor, this work presents a new hydraulic transducer configuration which improves the system's ability to capture a heartbeat signal from four subjects with different body weight and height, gender, age and cardiac history. It also proposes a new approach for detecting the occurrence of heartbeats from ballistocardiogram (BCG) signals through the use of the k-means clustering algorithm, based on finding the location of the J-peaks. Preliminary testing showed that the new transducer arrangement was able to capture the occurrence of heartbeats for all the participants, and the clustering approach achieved correct heartbeat detection ranging from 98.6 to 100% for three of them. Some considerations are discussed regarding adjustments that can be done in order to increase the correct detection of heartbeats for the participant whose percentage of correct detection ranged from 71.0 to 92.5%.

Robust inter-beat interval estimation in cardiac vibration signals

“…Compared to our previous work [6], as well as the works of other groups in the field [24,18], this is a fairly large data set. Not solely in terms of the number of subjects, but also with respect to the average recorded duration of approximately 6.5 hours.…”

“…Hence, reliably determining the location of individual heart beats in BCGs remains challenging. Other groups have often applied conceptually similar approaches, where either some form of template is learned [18,19] or a specific fiducial point is located [20]. As an exception, the authors of [7] suggest Fourier-domain averaging of multiple BCG channels together with a cepstrum analysis to estimate inter-beat-intervals.…”

Sensor Technology to Support Aging in Place

“…A new hydraulic bed sensor is under development at MU; it is in the process of deployment in TigerPlace now and preliminary data is exciting with more precise measurements of restlessness, respiration, and pulse. 24, 25 The more precise measurements will facilitate more accurate clinical judgments based on the sensor data by clinicians.…”

BESiDE

“…building layouts in delivery of social work services [4] and space syntax [5]). There is also a vast amount of research into monitoring peoples health [13]; the prevention of falls by older people [10] [11]; and technology to detect when falls have taken place [7].…”