Neha Mathur

Skin Temperature Prediction in Lower Limb Prostheses

Increased temperature and perspiration within a prosthetic socket is a common complaint of many amputees. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the socket and interface liner materials. These materials influence the bodys temperature regulation mechanism and might be the reason for thermal discomfort in prosthetic sockets. Monitoring interface temperature at skin level is notoriously complicated. The problem might be considered notorious because embedding wires and sensors in an elastomer eventually results in elastomer failures because of the high strain induced when donning a liner (amputees roll the liners onto their limbs). Another reason is because placing sensors and wires directly against the skin could cause irritation and chaffing over just a short period of time. We describe a route wherein if the thermal properties of the socket and liner materials are known, the in-socket residual limb temperature could be accurately predicted by monitoring the temperature between socket and liner rather than skin and liner using the Gaussian process technique.

Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses

Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring.

Issues in wearable mobile sensor platform for lower limb prosthetic users

Around the world health services are looking for ways of improving patient care for amputees suffering from diabetes, while at the same time reducing costs. These include remote monitoring of physiological data such as temperature, gait, heart rate, blood pressure, blood oxygenation (SpO2), respiration and glucose levels. The e-health wearable communication systems show promise in delivering improvements in patient care while at the same time reducing both the demand for resources and the financial burden on healthcare systems. These systems have the capability of monitoring, logging and transmitting the patient data to a central health authority. Depending on the patient, it is often critical that the monitoring system reliability is high to deliver the appropriate patient care and ensure patient safety. These wearable systems that would be placed in the prosthesis of the amputee are dependent on the battery power to drive them for continuous monitoring followed by data transmission. However, if improperly designed will rapidly deplete the battery energy making the system short lived and quickly prone to failure. Also, weight and size of the battery is a concern, as a heavier battery could induce discomfort to the amputee. In this paper, transmission system design and methods to reduce power consumption will be discussed using the example of prosthetic socket compatible temperature and gait monitoring data systems.

Wearable mobile sensor and communication platform for the in-situ monitoring of lower limb health in amputees

Monitoring the health of a residual limb in prosthesis is key to detect early signs of tissue injury, and could improve patient quality of life. However, monitoring at skin level could induce possible discomfort and irritation, making the skin susceptible for breakdown. The use of non-invasive sensor technologies within the flexible liner of the prosthetic device can alleviate these issues. The rehabilitation of lower limb prosthesis wearers can be greatly improved by a reliable continuous monitoring system that can alert both the user and health authority by early warning of the development of tissue damage. In this work, we have created a wearable sensor platform for lower limb amputees that is capable of gathering data from the sensors (placed on the elastomer), and store and transmit to a central health database, for the purpose of analyzing it. This paper explores the architecture used, as well as some of the challenges encountered when handling such quantities of data as experienced in this project.

Power supply issues in e-health monitoring applications

Recent years have seen a rapid growth in the development of e-health systems for the continuous remote patient monitoring of physiological data such as temperature, heart rate (HR), Blood pressure (BP), oxygenation (SpO2), respiration and glucose levels. The roll-out of such schemes show promise in delivering improvements in patient care while at the same time reducing both the demand for resources and the financial burden on healthcare systems. These wearable monitoring systems are used to monitor, log and transmit patient data to a central health authority. Depending on the patient, it is often critical that the monitoring system reliability is high to deliver the appropriate patient care and ensure patient safety. However, since wearable systems are solely dependent on battery power, continuous monitoring will rapidly deplete the battery energy making the system prone to failure. In this paper, methods to reduce power consumption will be discussed using the example of prosthetic socket temperature monitoring data.

A Practical Design and Implementation of a Low Cost Platform for Remote Monitoring of Lower Limb Health of Amputees in the Developing World

In many areas of the world accessing professional physicians “when needed/as needed” might not be always possible for a variety of reasons. Therefore, in such cases, a targeted e-Health solution to safeguard patient long-term health could be a meaningful approach. Todays modern healthcare technologies, often built around electronic and computer-based equipment, require an access to a reliable electricity supply. Many healthcare technologies and products also presume access to the high speed internet is available, making them unsuitable for use in areas where there is no fixed-line internet connectivity, access is slow, unreliable, and expensive, yet where the most benefit to patients may be gained. In this paper, a full mobile sensor platform is presented, based around readily-purchased consumer components, to facilitate a low cost and efficient means of monitoring the health of patients with prosthetic lower limbs. This platform is designed such that it can also be operated in a standalone mode, i.e., in the absence of internet connectivity, thereby making it suitable to the developing world. Also, to counter the challenge of power supply issues in e-Health monitoring, a self-contained rechargeable solution to the platform is proposed and demonstrated. The platform works with an Android mobile device, in order to allow for the capture of data from a wireless sensor unit, and to give the clinician access to results from the sensors. The results from the analysis, carried out within the platforms Raspberry Pi Zero, are demonstrated to be of use for remote monitoring. This is specifically targeted for monitoring the tissue health of lower limb amputees. The monitoring of residual limb temperature and gait can be a useful indicator of tissue viability in lower limb amputees especially those suffering from diabetes. We describe a route wherein non-invasive monitoring of tissue health is achievable using the Gaussian process technique. This knowledge will be useful in establishing biomarkers related to a possible deterioration in a patients health or for assessing the impact of clinical interventions.

Thermal time constant : optimizing the skin temperature predictive modelling in lower limb prostheses using Gaussian processes

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm – Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable.

Tissue viability monitoring - a multi-sensor wearable platform approach

Health services worldwide are seeking ways to improve patient care for amputees suffering from diabetes, and at the same time reduce costs. The monitoring of residual limb temperature, interface pressure and gait can be a useful indicator of tissue viability in lower limb amputees especially to predict the occurrence of pressure ulcers. This is further exacerbated by elevated temperatures and humid micro environment within the prosthesis which encourages the growth of bacteria and skin breakdown. Wearable systems for prosthetic users have to be designed such that the sensors are minimally obtrusive and reliable enough to faithfully record movement and physiological signals. A mobile sensor platform has been developed for use with the lower limb prosthetic users. This system uses an Arduino board that includes sensors for temperature, gait, orientation and pressure measurements. The platform transmits sensor data to a central health authority database server infrastructure through the Bluetooth protocol at a suitable sampling rate. The data-sets recorded using these systems are then processed using machine learning algorithms to extract clinically relevant information from the data. Where a sensor threshold is reached a warning signal can be sent wirelessly together with the relevant data to the patient and appropriate medical personnel. This knowledge is also useful in establishing biomarkers related to a possible deterioration in a patient’s health or for assessing the impact of clinical interventions.

Thermal time constant: improving the accuracy of skin temperature predictive modelling in lower limb prostheses

This is the dataset linked to: Tang, Jing et al (2015) Use of gait lab 3D motion capture for dynamic assessment of amputee socket interface biomechanics – a preliminary study. Prosthetics and Orthotics International, 39, (1), supplement 2-608, 257. doi:10.1177/0309364615591101).Background: Sierra Leone is a low income country in West Africa that has a history of conflict. Sierra Leone have signed and ratified the Convention of Rights of Persons with Disabilities. Aim: To evaluate persons with disability that use prosthetic and orthotic assistive devices access to human rights. The addressed areas were; right to health, right to a standard of living adequate for health, right to vote, right to marry and found a family, right to education, right to work and. A further aim was to compare groups of participants regarding gender, area of residence, income and type and level of device. Methods: Questionnaires were used to collect self-reported data from 139 prosthetic and orthotic users in Sierra Leone. Results: About half of the patient considered their overall physical health as good or very good. Thirty-seven percent of the participants said their mental health is bad or very bad. The majority said they did not have access to medical care and the most common reason given was that they could not afford doctors fee. The orthotic users reported they required medical care outside home more often than the prosthetic users. About half of the participants could not access afford medication when they needed it. About half of the participants had regularly access to safe drinking water and only 10% had the possibility to eat three times a day. The majority had a reasonably or adequate house to live. Half of the participants were married and 70% had children. Almost all reported that they could vote if they wanted. About half were working but often self-employed with small business. Sixty percent could read and write. Discussion & Conclusion: There was still a need for significant progress in increased access to medical care and medication when needed for persons with lower limb physical disability in Sierra Leone. Increased access to food and clean water to facilitate an acceptable standard of living adequate for health were also necessary in order to strive towards implementing the rights to health for persons with disability.Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health [1]. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. This leads to a hypothesis that if the thermal properties of the socket & liner materials are known then the in-socket skin temperature could be accurately predicted by measuring between the socket and interface liner, rather than at the more technically challenging skin interface.Book 7th Annual International Conference on Business, Law & Economics 4-7 May 2020, Athens, Greece Edited by Gregory T. Papanikos THE ATHENS INSTITUTE FOR EDUCATION AND RESEARCH