Plantar foot temperature during sitting and standing in participants with diabetes and controls

  • Christopher Beach (Contributor)
  • Glen Cooper (Contributor)
  • Andrew Weightman (Contributor)
  • Emma Hodson-Tole (Creator)
  • Neil D. Reeves (Creator)
  • Alex Casson (Contributor)
  • Emma Hodson-Tole (Contributor)



Continuous temperature data collected from the plantar (sole) of the foot of 13 participants with diabetes and 12 healthy control participants during sitting and standing. Collected with our custom personalised temperature sensing insoles (see paper for description).

If using this data please cite: Beach, C.; Cooper, G.; Weightman, A.; Hodson-Tole, E.F.; Reeves, N.D.; Casson, A.J. Monitoring of Dynamic Plantar Foot Temperatures in Diabetes with Personalised 3D-Printed Wearables. Sensors 2021, 21, 1717.

The data presented here has been converted into °C and filtered using a low-pass filter with cut-off frequency of 0.02 Hz.

Temperature data is provided in csv format and the participant metadata is in xlsx format. In addition data is provided in Python serialized (pickle) format to allow easy importing to Python (see below for steps to do this). Use of the Anaconda Distribution is recommended.

In the metadata, Testing Date 1 refers to date where pressure mat data was collected to inform the personalised insole design. Testing Date 2 refers to the date where the temperature data uploaded here was collected.

To import this data into Python use the following commands:
import numpy as np
import pandas as pd
import pickle as pkl
with open('participants.pkl', 'rb') as f:
participants= pkl.load(f) # This line needs to be indented, however Mendeley is removing this formatting

'participants' is then a dictionary containing dictionaries for each participants. Within each of these dictionaries are four Pandas DataFrame's containing the temperature data for each foot, for sitting and standing.
For example, if you wanted to access the DataFrame for the left foot of participant H1 during standing you would type:

Within each DataFrame each column corresponds to:
Time: The timestamp of each datapoint in HH:MM:SS as recorded by the iPhone app
Ch0: Temperature data from the Hallux
Ch1: Temperature data from the 1st Metatarsal Head
Ch2: Temperature data from the 5th Metatarsal Head
Ch3: Temperature data from the Calcaneus

So if you wanted just the temperature data from the left 1st Metatarsal Head of participant H1 during sitting you would type:
Date made available2 Mar 2021
PublisherMendeley Data

Research Beacons, Institutes and Platforms

  • Manchester Environmental Research Institute
  • Manchester Institute for Collaborative Research on Ageing


  • 3D printing
  • diabetes
  • diabetic foot
  • peripheral neuropathy
  • digital health
  • personalised medicine
  • foot temperature monitoring
  • telehealth
  • wearables

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