Detection of respiratory waveforms using non-contact electrodes during bathing

Death rate of accidental drowning in the bathtub was the highest among casualties occurring at home, according to the annual report of the Japanese Ministry of Health, Labour and Welfare in 2007. To prevent accidental drowning during bathing at home, we obtained respiratory waveforms from bioelectric impedance (BEI) measurement using non-contact electrodes. The BEI measurement is an involuntary measurement method, from which respiratory waveform during bathing can be extracted. In the present study, to find the most appropriate electrode configuration as well as the optimal measuring frequency, we calculated the frequency dependence of impedance amplitude by numerical technique based on a three-dimensional finite difference method for a composite system consisting of a human body submerged in bath water. The results of model calculation agreed with the experimental results. Next, to obtain respiratory waveforms with large amplitudes, we investigated the optimal frequency experimentally. The frequency of 1 MHz was suitable for involuntary measurement of respiratory waveform during bathing.

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Development of Personal Identification Method by Changes in the Foot Load and Trajectory of the Center of Foot Pressure When Opening a Door

Nasu¹,

Kim²,

Nakajima³

2014

Transactions of the Society of Instrument and Control Engineers

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Sensor systems have been developed that can automatically obtain physiological data in bathrooms and toilet stalls. In order to measure the physiological data of individuals who live with a number of other people, each person has to be identified separately. However, it is difficult to obtain active user cooperation. Ideally, personal identification should be achieved without requiring subjects to cooperate. Therefore, we measured changes in the load and trajectory of the center of foot pressure when opening a door by utilizing the features of a Nintendo R Wii balance board as a load sensor. We calculated the Euclidean distance between the registered data and the test data. Personal identification was achieved by using the nearest neighbor algorithm. Data generated while walking through a door were obtained for five subjects, yielding an identification rate of 93.7%.

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Detection of respiratory waveforms using non-contact electrodes during bathing

Cited by 3 publications

References 6 publications

Electrodes array for contactless ECG measurement of a bathing person - a sensitivity analysis

Electrodes array for contactless ECG measurement of a bathing person - a sensitivity analysis

Involuntary Measurement System for Respiratory Waveform for Prevention of Accidental Drowning during Bathing

Development of Personal Identification Method by Changes in the Foot Load and Trajectory of the Center of Foot Pressure When Opening a Door

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