Abstract: The present disclosure provides a method for sweat volume detection based on sweat print imaging, comprising: obtaining a raw data set, the raw data set including at least one sweat print image formed by dropping different volumes of sweat on a test paper under different environmental parameters; obtaining a color value extreme of the sweat print image and dividing the sweat print image into at least one region; calculating a sweat error based on a total sweat collection volume and a real sweat volume; obtaining a trained error prediction model; obtaining a to-be-tested sweat print image and current environmental parameters; inputting the current environmental parameters and a count of regions of the to-be tested sweat print image into the trained error prediction model to determine a sweat error of the to-be-tested sweat print image; calculating a sweat volume and a sweat rate based on the sweat error.

Abstract: The present disclosure provides a method for sweat volume detection based on sweat print imaging, comprising: obtaining a raw data set, the raw data set including at least one sweat print image formed by dropping different volumes of sweat on a test paper under different environmental parameters; obtaining a color value extreme of the sweat print image and dividing the sweat print image into at least one region; calculating a sweat error based on a total sweat collection volume and a real sweat volume; obtaining a trained error prediction model; obtaining a to-be-tested sweat print image and current environmental parameters; inputting the current environmental parameters and a count of regions of the to-be tested sweat print image into the trained error prediction model to determine a sweat error of the to-be-tested sweat print image; calculating a sweat volume and a sweat rate based on the sweat error.