Data-Raspberry data for 'Wearable multimodal skin sensing for the diabetic foot'

This data is supplied in support of the the article "Wearable multimodal skin sensing for the diabetic foot" by Coates, Chipperfield and Clough in the open access journal 'electronics - Raspberry Pi Special edition'. A data set is provided for each volunteer referenced as 001, 009 and 1001 are enclosed. Biomentric data is supplied for each volunteer along with the data set used in the article. The title of each graph presented in the article identifies the data set used together with the chosen data filter type (low pass) and filter cut off frequency. TA 6 pole Butterwoth filter was used. Data was analysed in Python Spyder 2.3.5.2. Data is taken in time series with a descriptor of the data stream collected in row 5 of the respective column. The unis for each data stream is in row 6. All data ws taken at 20Hz.