Abstract
Aging women usually experience menopause and currently there is no single diagnosing highly-sensitive and -specific test for recognizing menopause. For most employed women at their perimenopause age it is not convenient to visit a clinic for the hormone test, which lasts for consecutive days. This paper develops a suit of sensor-based smart clothing used for home-based and ambulatory health monitoring for women’s menopause transition. Firstly, a survey analysis is conducted to determine the biological signals measured by sensors for indicating the symptoms of menopausal transition and also the body areas with salient symptoms to implant the sensors on the clothing. Then, the smart clothing is designed with a set of temperature and relative humidity sensors on different locations and with a microcontroller to transmit the measured data to the computer. With the smoothed data as input, a new detection algorithm for hot flashes is proposed by recognition of the concurrent occurrence of heat and sweating rise/down, and can figure out the frequency, intensity, and duration—triple dimension information of a hot flash, which is helpful to achieve precise diagnosis for menopausal transition. The smart clothing and the detection algorithm are verified by involving a group of women subjects to participate in a hot flash monitoring experiment. The experimental results show that this smart clothing monitoring system can effectively measure the skin temperature and relative humidity data and work out the frequency, duration, and intensity information of a hot flash pertaining in different body areas for individuals, which are accordant with the practice reported by the subjects.
Highlights
Menopause is a universal biological event among aging women and happens to normal women at a mean age of 51; reports indicate that, 95% of women become menopausal between 45 and years of age [1]
We develop a suit of sensor-based smart clothing for convenient and sensitive monitoring of menopausal transition for employed women
According to the number of the relative humidity sensors with temperature output (RH/T) sensors, skin noise and vibration along with the distribution, which may generate abnormal data outliers or deviation temperature and relative humidity data accompanied by time information are stored in different errors in data, complicate the analysis of the trends of skin temperature and relative humidity files
Summary
Menopause is a universal biological event among aging women and happens to normal women at a mean age of 51; reports indicate that, 95% of women become menopausal between 45 and years of age [1]. We develop a suit of sensor-based smart clothing for convenient and sensitive monitoring of menopausal transition for employed women. When this clothing is worn, the attached sensors automatically gather skin temperature and relative humidity data from different body areas. The detection algorithm can output useful detection information including frequency, duration, and intensity of hot flashes, whereas previous work was merely concerned with frequency These detection results offer precise diagnosis for menopausal transition and are consistent with the practical symptoms of the involved subjects.
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