Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Design and Characterization of a Helmet-Based Smart Textile Pressure Sensor for Concussion

Version 1 : Received: 25 July 2020 / Approved: 26 July 2020 / Online: 26 July 2020 (02:34:43 CEST)

How to cite: Alkhader, A.S.; Saikia, M.J.; Driscoll, B.; Mankodiya, K. Design and Characterization of a Helmet-Based Smart Textile Pressure Sensor for Concussion. Preprints 2020, 2020070629 (doi: 10.20944/preprints202007.0629.v1). Alkhader, A.S.; Saikia, M.J.; Driscoll, B.; Mankodiya, K. Design and Characterization of a Helmet-Based Smart Textile Pressure Sensor for Concussion. Preprints 2020, 2020070629 (doi: 10.20944/preprints202007.0629.v1).

Abstract

A Mild traumatic brain injury (mTBI) or concussion has become a public health problem in the United State. Sports and recreational activities are major sources of concussions; with the most incidents connected to American football. Recently, many companies and research institutions have started studying concussions and introduced some means of protection and some alarming systems of strong jolts. The major detection and protection system currently available on the market is the electronic helmet (e-helmet) composed of measurement devices to record head impact acceleration. The most commonly used devices in e-helmets are accelerometers to measure linear acceleration and gyroscopes for rotational/angular acceleration. Using smart textiles for concussion detection is currently uncommon and limited due to the lack of literature studying their voltage related errors. Actually, there are few works that characterize some voltage-force related errors for such type of sensors but for small impact forces and under bench testing while the behavior of those sensors was not described for higher ranges of applied forces and in field situations. This paper previews some common techniques used in e-helmets for concussion detection and highlights electronic textiles and smart fabric sensors that could be very useful for these applications. It discusses and validates the general behavior of such type of sensors under high impact forces and on field testing instead of bench testing, and also it characterizes the effect of increasing the thickness of the sensing element layer on the sensor. A custom-made pressure sensor was created of some available fabrics to be embedded within the padding of a football helmet to quantify the impacting force to the head. The sensor is mainly composed a Semi Conductive Polymer Composite SCPC layer with modifiable thickness that was modified three times with 0.2, 0.4, and 1.6mm to characterize the general behavior of the sensor due to a high amount of impacts and correlated with the thickness. A pendulum system was built to test the pressure sensors, while a special camera and an open-source video analysis software, Tracker was used to track the pendulum bob. The speed and the acceleration of the pendulum bob were measured, then the impact force was calculated and a voltage-force response was obtained. The results showed that no meaningful improvement occurs by small increase in the thickness but better sensor behavior could be obtained by significant increment to observe any difference. Despite that at a very high impacts, the suggested sensor with Velostat layers is not giving the real voltage readings that reflect the actual applied forces but it gives a helpful information that illustrate the distribution of the force through identification the place of the highest and lowest voltage readings regardless of the exact values of those readings. However, the proposed smart textile pressure sensor could be applicable in future e-helmet designs with additional research-based improvements especially on the structure of the sensing element layer to be able to withstand such high impacts which in turns improves the overall sensor performance and accurately measures pressure in concussion-inducing ranges.

Subject Areas

smart textiles; pressure sensor; concussion detection; Velostat; football helmet; head impacts

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