Design and Implementation of a Smart Insole System to Measure Plantar Pressure and Temperature

Abstract

An intelligent insole system may monitor the individual’s foot pressure and temperature in real-time from the comfort of their home, which can help capture foot problems in their earliest stages. Constant monitoring for foot complications is essential to avoid potentially devastating outcomes from common diseases such as diabetes mellitus. Inspired by those goals, the authors of this work propose a full design for a wearable insole that can detect both plantar pressure and temperature using off-the-shelf sensors. The design provides details of specific temperature and pressure sensors, circuit configuration for characterizing the sensors, and design considerations for creating a small system with suitable electronics. The procedure also details how, using a low-power communication protocol, data about the individuals’ foot pressure and temperatures may be sent wirelessly to a centralized device for storage. This research may aid in the creation of an affordable, practical, and portable foot monitoring system for patients. The solution can be used for continuous, at-home monitoring of foot problems through pressure patterns and temperature differences between the two feet. The generated maps can be used for early detection of diabetic foot complication with the help of artificial intelligence.

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

“…Notably, the use of pose estimation was particularly advantageous in overcoming the limitations of wearable devices attached to the body for measuring changes in the positions of body joints 18,36 . On the other hand, the smart insole excelled in capturing subtle pressure changes under the feet, enabling a more detailed differentiation of walking phases 37,38 …”

“…18,36 On the other hand, the smart insole excelled in capturing subtle pressure changes under the feet, enabling a more detailed differentiation of walking phases. 37,38 In summary, the integration of AI-based detection tools and wearable technologies, including smart insoles and IMU-equipped earbuds, is profoundly reshaping patient care through real-time data acquisition. The amalgamation and effective utilization of such data have the potential to enhance the accuracy of diagnosis, prediction and treatment across a spectrum of conditions, including sarcopenia.…”

Hotspots: Adherence in home foot temperature monitoring interventions for at‐risk feet with diabetes—A narrative review

“…When combined with advancements in machine learning, 31 and wearables for tracking adherence in wearing therapeutic footwear 32,33 this may offer new opportunities to extract new physical activity metrics such as daily steps at moderate or vigorous intensity, steps taken in correctly fitting footwear or coefficient of variation in daily steps which may enable us to refine HFTM interventions further. Equally, in recent years, a number of prototype insoles have emerged which are capable of measuring foot temperatures without the need for laborious manual infrared thermometer measurements 34–36 . The key to this future will lie both in integrating these technologies to minimise the burden upon those wearing them (battery charging, number of apps which need to be downloaded and learned etc.)…”

“…Equally, in recent years, a number of prototype insoles have emerged which are capable of measuring foot temperatures without the need for laborious manual infrared thermometer measurements. [34][35][36] The key to this future will lie both in integrating these technologies to minimise the burden upon those wearing them (battery number of apps which need to be downloaded learned etc.) and of daily step targets taking account of individual free time, or temperature monitoring of previous ulcer locations.…”

Artificial Intelligence Methodologies Applied to Technologies for Screening, Diagnosis and Care of the Diabetic Foot: A Narrative Review

“…It is worth noting that some studies already moved in the direction of integrating different sensors for diabetic foot monitoring. Specifically, some recent studies the proposed integration of temperature and pressure sensing, plus, possibly, glucose levels in sweat [ 90 , 91 ]. However, as stated above, skin resistance and humidity sensors should be integrated; we suggest that there should be at least two resistance sensors for each foot, one possibly placed between the second and third metatarsal head regions, and one between the lateral and medial heel regions, whereas at least one humidity sensor per foot should be used, possibly placed between the lateral and medial midfoot regions.…”