Method for measuring weight value in sleep state by steady-state duration confidence

Abstract

The invention discloses a method for measuring body weight in a sleep state through the steady-state duration confidence degree. A plurality of pressure sensors are arranged under the bed, and the duration of a measurement period is determined; a long-time window is defined, and the long-time window is used to judge Steady state; when the steady state of the bed state ends, determine the steady state body weight of the user during the steady state, and calculate the steady state duration confidence as the reference value for calculating the steady state confidence. The steady state confidence; in After the measurement period ends, one or more steady-state body weights are selected according to the steady-state confidence to calculate the user's period weight in the measurement period. In the present invention, by dividing the long-time window and judging whether the long-time window is a steady state method, the steady-state duration and the steady-state duration confidence can be calculated, and the steady-state body weight can be obtained; the steady-state duration confidence can be used to evaluate each The reliability of the steady-state body weight can then obtain a weight value that can represent the user's actual weight, and provide accurate weight data for basic health monitoring.

Description

technical field [0001] The invention relates to the field of basic health monitoring, in particular to a method for measuring body weight in a sleep state through steady-state duration confidence. Background technique [0002] The accuracy of traditional electronic weighing scales is generally 0.1kg. Under this accuracy, the reading is relatively easy to stabilize. Once stable, the electronic weighing scale can output it to the display screen, and it seems that only one value is read. In fact, with any electronic weighing device, the readings obtained are a sequence, not a single value. Since basic health monitoring needs to obtain high-precision weight data of the user in order to analyze and monitor the health status, a high-precision pressure sensor below 10g is generally used, and the measurement of the pressure sensor is a dynamic process. As long as a certain accuracy is achieved, a slight disturbance will Different readings are generated. Assuming that a measurement ...

AI Technical Summary

Problems solved by technology

Since basic health monitoring needs to obtain high-precision weight data of the user in order to analyze and monitor the health status, a high-precision pressure sensor below 10g is generally used, and the measurement of the pressure sensor is a dynamic process. As long as a certain accuracy is achieved, a slight disturbance will Different readings are generated. Assuming that a measurement is performed every second, different readings will be generated every second, so that the weight data is difficult to stabilize. For example, the user stays in bed for 8 hours, that is, 8×60×60=28800 seconds Will produce 28,800 weighing readings; making it difficult to judge which weighing data more accurately reflects the user's actual weight

[0003] In addition, the actions of a person on the bed, such as: going to bed, getting out of bed, turning over, etc., will have an impact on the readings of the pressure sensor, resulting in large instantaneous fluctuations; if these effects are not eliminated, the measured weight value will produce large distortion

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