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. 2020 Sep 14;19(1):71.
doi: 10.1186/s12938-020-00814-y.

A personalised prosthetic liner with embedded sensor technology: a case study

Affiliations

A personalised prosthetic liner with embedded sensor technology: a case study

Linda Paternò et al. Biomed Eng Online. .

Erratum in

Abstract

Background: Numerous sensing techniques have been investigated in an effort to monitor the main parameters influencing the residual limb/prosthesis interface, fundamental to the optimum design of prosthetic socket solutions. Sensing integration within sockets is notoriously complex and can cause user discomfort. A personalised prosthetic liner with embedded sensors could offer a solution. However, to allow for a functional and comfortable instrumented liner, highly customised designs are needed. The aim of this paper is to presents a novel approach to manufacture fully personalised liners using scanned three-dimensional image data of the patient's residual limb, combined with designs that allow for sensor integration. To demonstrate the feasibility of the proposed approach, a personalised liner with embedded temperature and humidity sensors was realised and tested on a transtibial amputee, presented here as a case study.

Methods: The residual limb of a below knee amputee was first scanned and a three-dimensional digital image created. The output was used to produce a personalised prosthesis. The liner was manufactured using a cryogenic Computer Numeric Control (CNC) machining approach. This method enables fast, direct and precise manufacture of soft elastomer products. Twelve Hygrochron Data Loggers, able to measure both temperature and humidity, were embedded in specific liner locations, ensuring direct sensor-skin contact. The sensor locations were machined directly into the liner, during the manufacturing process. The sensors outputs were assessed on the below amputee who took part in the study, during resting (50 min) and walking activities (30 min). To better describe the relative thermal properties of new liner, the same tests were repeated with the amputee wearing his existing liner. Quantitative comparisons of the thermal properties of the new liner solution with that currently used in clinical practice are, therefore, reported.

Results: The liner machining process took approximately 4 h. Fifteen minutes after donning the prosthesis, the skin temperature reached a plateau. Physical activity rapidly increased residuum skin temperatures, while cessation of activity caused a moderate decrease. Humidity increased throughout the observation period. In addition, the new liner showed better thermal properties with respect to the current liner solution (4% reduction in skin temperature).

Conclusions: This work describes a personalised liner solution, with embedded temperature and humidity sensors, developed through an innovative approach. This new method allows for a range of sensors to be smoothly embedded into a liner, which is capable of measuring changes in intra-socket microclimate conditions, resulting in the design of advanced socket solutions personalised specifically for individual requirements. In future, this method will not only provide a personalised liner but will also enable dynamic assessment of how a residual limb behaves within the socket during daily activities.

Keywords: Cryogenic CNC machining; Humidity; Lower limb; Prosthetic liner; Prosthetic socket; Temperature; Transtibial amputation.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Sensing systems mounting techniques for interface measurements within transtibial prosthetic socket: integrating sensors on the socket wall (a) in contact with the skin or (b) with the prosthetic liner; (c) inserting sensors within the socket; (d) embedding the sensors into the socket wall (adapted by [11])
Fig. 2
Fig. 2
Example of the linear regression for the temperature (T) (left) and the relative humidity (RH) (right) measured by one iButton and the climate chamber during the calibration process. Considering all the iButtons, the linear regression resulted in a mean slope coefficient equal to 1.00 ± 0.01 for the temperature (range: 0.89–1.07) and to 0.88 ± 0.013 for the relative humidity (range: 0.83–0.91). The mean intercept was 0.36 ± 0.11 for the temperature (range: − 1.84 to 4.87) and 6.98 ± 0.51 for the relative humidity (range: 5.70–9.12)
Fig. 3
Fig. 3
a, b CAD and Neoprene foam prototype of the new personalised liner with specific enclosures designed to embed the Hygrochron Data Loggers iButtons; c the two refined halves of the new personalised liner with the twelve embedded Hygrochron Data Loggers covered with the layer of breathable yet waterproof fabric; d the final personalised liner prototype
Fig. 4
Fig. 4
Left top corner: Test image acquired by the thermo-camera at the end of the test session (the image has been recorded in the frontal view at the end of the protocol). Right top corner: iButtons positions on the residual limb during the test session (anterior and posterior views). Bottom: Temperature and relative humidity values within the prosthetic socket with the new liner. The vertical lines indicate the different 1-min stages used to analyse the data: RP1start, first minute of the 1st resting period (test minute 1); RP1end, last minute of the 1st resting period (test minute 50); PA, last minute of walking on the treadmill (test minute 80); RP2end, last minute of the 2nd resting period (test minute 130). Temperature and humidity room conditions are reported in red on the top of the graphs
Fig. 5
Fig. 5
Left top corner: Test image acquired by the thermo-camera at the end of the test session with the patient’s Pe-Lite liner (the image has been recorded in the frontal view at the end of the protocol). Right top corner: iButtons positions on the residual limb during the test session (anterior and posterior views). Bottom: Temperature and relative humidity values within the prosthetic socket with the Pe-Lite liner. The vertical lines indicate the different 1-min stages used to analyse the data: RP1start, first minute of the 1st resting period (test minute 1); RP1end, last minute of the 1st resting period (test minute 50); PA, last minute of walking on the treadmill (test minute 80); RP2end, last minute of the 2nd resting period (test minute 130). Temperature and humidity room conditions are reported in red on the top of the graphs
Fig. 6
Fig. 6
a Hygrochron Data Loggers (Type: DS1923-F5#) and b data acquisition system. c Hygrochron Data Loggers with the layer of breathable yet waterproof fabric; d Scan of residual limb with twelve Hygrochron Data Loggers positioned on; e Scan of the Pe-Lite liner; f Scan of the residual limb; g Alignment process; h Alignment result; i Final design of the new personalised liner with specific enclosures in the internal surface for the Hygrochron Data Loggers
Fig. 7
Fig. 7
a The new ad hoc personalised liner with embedded sensors and b its fitting on the residual limb; c The modified SILOSHEATH™ prosthetic sheath with specific holes and d with the sensors in the same positions of the ad hoc personalised liner and e its fitting in the usual patient’s socket system

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