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

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

Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for 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

Toward novel wearable pyroelectric temperature sensor for medical applications

Knowledge of an amputees’ residual limb skin temperature is considered to be of particular importance as an indicator of tissue health. Temperature within the prosthetic socket typically varies over the range 25°C to 35°C and this warm, confined environment causes sweating which creates favourable conditions for both the growth of bacteria and an increased risk of tissue breakdown. With this in mind a wearable sensor for the real-time measurement of temperature variations at the prosthetic socket/liner interface is under development and a proof of concept prototype is presented. The sensor exploits the large pyroelectric effect present in ferroelectric lead zirconate titanate (PbZr)x (Ti)(1-x)(O3) (PZT) and has several inherent advantages over other methods of temperature sensing. The sensing element is a low cost commercially available thick-film PZT device. Mathematical models are developed to describe the sensor immitance and response to temperature change, and both the clamped and unclamped capacitances are investigated over the range 20°C to 40°C. Sensor characteristics were found to be dominated by the clamped dielectric constant and operation under short-circuit conditions is found to offer a constant sensor gain over the temperature range of interes

Exploring the role of transtibial prosthetic use in deep tissue injury development : a scoping review

Background: The soft tissue of the residual limb in transtibial prosthetic users encounters unique biomechanical challenges. Although not intended to tolerate high loads and deformation, it becomes a weight-bearing structure within the residuum-prosthesis-complex. Consequently, deep soft tissue layers may be damaged, resulting in Deep Tissue Injury (DTI). Whilst considerable effort has gone into DTI research on immobilised individuals, only little is known about the aetiology and population-specific risk factors in amputees. This scoping review maps out and critically appraises existing research on DTI in lower-limb prosthetic users according to (1) the population-specific aetiology, (2) risk factors, and (3) methodologies to investigate both. Results: A systematic search within the databases Pubmed, Ovid Excerpta Medica, and Scopus identified 16 English-language studies. The results indicate that prosthetic users may be at risk for DTI during various loading scenarios. This is influenced by individual surgical, morphological, and physiological determinants, as well as the choice of prosthetic componentry. However, methodological limitations, high inter-patient variability, and small sample sizes complicate the interpretation of outcome measures. Additionally, fundamental research on cell and tissue reactions to dynamic loading and on prosthesis-induced alterations of the vascular and lymphatic supply is missing. Conclusion: We therefore recommend increased interdisciplinary research endeavours with a focus on prosthesis-related experimental design to widen our understanding of DTI. The results have the potential to initiate much-needed clinical advances in surgical and prosthetic practice and inform future pressure ulcer classifications and guidelines

Transtibial prosthetic users as a risk group for deep tissue injuries

The replacement of the lower leg with a transtibial prosthesis poses a high biomechanical challenge for the surrounding body structures: Loads that are usually distributed across the skeletal system are now transferred to the prosthesis via soft tissues. Since those tissue layers are not physiologically adapted to be weight-bearing structures, amputees might develop Deep Tissue Injuries (DTI). To gain a better understanding of the underlying processes and population-specific influences, we aimed to map out and analyse existing research on aetiology and risk factors for DTI in transtibial amputees, and highlight open questions

Thermal time constant: optimising 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

Accuracy Verification of Magnetic Resonance Imaging (MRI) Technology for Lower-Limb Prosthetic Research: Utilising Animal Soft Tissue Specimen and Common Socket Casting Materials

Lower limb prosthetic socket shape and volume consistency can be quantified using MRI technology. Additionally, MRI images of the residual limb could be used as an input data for CAD-CAM technology and finite element studies. However, the accuracy of MRI when socket casting materials are used has to be defined. A number of six, 46 mm thick, cross-sections of an animal leg were used. Three specimens were wrapped with Plaster of Paris (POP) and the other three with commercially available silicone interface liner. Data was obtained by utilising MRI technology and then the segmented images compared to corresponding calliper measurement, photographic imaging, and water suspension techniques. The MRI measurement results were strongly correlated with actual diameter, surface area, and volume measurements. The results show that the selected scanning parameters and the semiautomatic segmentation method are adequate enough, considering the limit of clinical meaningful shape and volume fluctuation, for residual limb volume and the cross-sectional surface area measurements

Has silicon reached its limit?

In light of the rapidly increasing demand for ultra-high speed data transmission, data centres are under pressure to provide ever increasing data transmission through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present electronic switching technology using current data centre architecture is becoming increasingly difficult to scale despite improvements in data management. In this paper the tremendous bandwidth potential of optical fibre based networks will be explored alongside the issues of electronic scalability and switching speed. A resulting need for alternative optical solutions for all-optical signal processing systems will be discussed. With this in mind, progress in the form of a novel and highly scalable optical interconnect will be reviewed

Utilising the repertory grid technique in visual prosthetic design : promoting a user-centred approach

This paper proposes a new User-Centred data-collection methodology based on the 9 Repertory Grid Technique (RGT) for the aesthetic design of below-knee prostheses. The innovation of 10 this methodology is to propose a measurable approach guiding the designer to detect latent emotional needs of interviewed prosthetic users to be translated into measurable aesthetic issues to reproduce in their customized devices. This work is situated within the Kansei Engineering framework and is part of a more comprehensive study for the revision of aesthetic prosthetic design. The data of this paper are based on face to face interviews and the results were translated into a set of design principles and elements classifying the statements of the users. This methodology aims to stand as an initiative for a new design system for the improvement of the emotional User Experience of prosthetic users – and to consequently provide products to be positively accepted by the users for the improvement of their body image

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