Back cushion for detecting emotional stress in non-contact mode based on heart rate variability

Abstract

The invention provides a back cushion for detecting emotional stress in a non-contact mode based on heart rate variability. The back cushion comprises a back cushion body, a data operation box installed on the back cushion body and a piezoelectric sensor which is installed in the back cushion body and in contact with the data operation box. The back cushion for detecting the emotional stress in the non-contact mode based on the heart rate variability is simple in structure and convenient to use, through cooperation of the piezoelectric sensor arranged in the back cushion and the data operationbox, on the premise that the back cushion keeps indirect contact with a user, body vibration transduction signals of the user can be acquired, stress signals are acquired by the piezoelectric sensorthrough the data operation box and are processed, HRV parameters included in the stress signals are calculated, by matching the HRV parameters with index models, emotional stress, stress tolerance andthe fatigue index of a testee are analyzed, therefore the emotional stress and the body state of the user can be monitored at any time, intervention is conveniently and timely conducted, and the state of the user is prevented from continuing to deteriorate.

Description

technical field [0001] The invention relates to emotional pressure monitoring equipment, in particular to a cushion for non-contact detection of emotional pressure based on heart rate variability. Background technique [0002] Heart rate variability (HRV) refers to the change of heart rate rhythm over time. HRV is to analyze the subtle time changes and their regularity of each cardiac cycle. This kind of change is often difficult to detect on the conventional electrocardiogram recorded on the body surface or is negligible because it is small. The regular sinus rhythm that is customarily described on the conventional electrocardiogram is by no means equal to the absence of heart rate variation. The research object of HRV is only the time difference between successive cardiac cycles. Listing the differences between each cardiac cycle in the human body can show that a large number of seemingly disordered parameters reflect the continuous instantaneous fluctuation of heart rate...

AI Technical Summary

Problems solved by technology

However, the system uses complex image recognition technology and algorithms, and the entire system is expensive and difficult to promote

However, because the physiological signals of the ballistocardiogram (BCG) collected by the piezoelectric sensor are passively sensed, the obtained signals are complicated and difficult to process. At present, there is no good processing method, and many studies are ultimately due to the inability to deal with the complicated cardiac shocks. Figure (BCG) signal, but can not obtain accurate HRV signal, and thus can not achieve industrialization

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