Seismocardiogram (SCG) or mechanocardiography is a noninvasive cardiac diagnostic method; however, previous studies used only a single sensor to detect cardiac mechanical activities that will not be able to identify location-specific feature points in a cardiac cycle corresponding to the four valvular auscultation locations. In this study, a multichannel SCG spectrum measurement system was proposed and examined for cardiac activity monitoring to overcome problems like, position dependency, time delay, and signal attenuation, occurring in traditional single-channel SCG systems. ECG and multichannel SCG signals were simultaneously recorded in 25 healthy subjects. Cardiac echocardiography was conducted at the same time. SCG traces were analyzed and compared with echocardiographic images for feature point identification. Fifteen feature points were identified in the corresponding SCG traces. Among them, six feature points, including left ventricular lateral wall contraction peak velocity, septal wall contraction peak velocity, transaortic peak flow, transpulmonary peak flow, transmitral ventricular relaxation flow, and transmitral atrial contraction flow were identified. These new feature points were not observed in previous studies because the single-channel SCG could not detect the location-specific signals from other locations due to time delay and signal attenuation. As the results, the multichannel SCG spectrum measurement system can record the corresponding cardiac mechanical activities with location-specific SCG signals and six new feature points were identified with the system. This new modality may help clinical diagnoses of valvular heart diseases and heart failure in the future.

Body posture and activity are important indices for assessing health and quality of life, especially for elderly people. Therefore, an easily wearable device or instrumented garment would be valuable for monitoring elderly people’s postures and activities to facilitate healthy aging. In particular, such devices should be accepted by elderly people so that they are willing to wear it all the time. This paper presents the design and development of a novel, textile-based, intelligent wearable vest for real-time posture monitoring and emergency warnings. The vest provides a highly portable and low-cost solution that can be used both indoors and outdoors in order to provide long-term care at home, including health promotion, healthy aging assessments, and health abnormality alerts. The usability of the system was verified using a technology acceptance model-based study of 50 elderly people. The results indicated that although elderly people are anxious about some newly developed wearable technologies, they look forward to wearing this instrumented posture-monitoring vest in the future.

In this work, a wearable smart clothing system for cardiac health monitoring with a multi-channel mechanocardiogram (MCG) has been developed to predict the myo-cardiac left ventricular ejection fraction (LVEF) function and to provide early risk warnings to the subjects. In this paper, the realization of the core of this system, i.e., the Cardiac Health Assessment and Monitoring Platform (CHAMP), with respect to its hardware, firmware, and wireless design features, is presented. The feature values from the CHAMP system have been correlated with myo-cardiac functions obtained from actual heart failure (HF) patients. The usability of this MCG-based cardiac health monitoring smart clothing system has also been evaluated with technology acceptance model (TAM) analysis and the results indicate that the subject shows a positive attitude toward using this wearable MCG-based cardiac health monitoring and early warning system.

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