USABILITY OF TEXTILE-INTEGRATED ELECTRODES FOR EMG MEASUREMENTS

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USABILITY OF TEXTILE-INTEGRATED ELECTRODES FOR EMG MEASUREMENTS Niina Lintu University of Kuopio, Department of Physiology, Laboratory of Clothing Physiology, Kuopio, Finland Jaana Holopainen & Osmo Hänninen University of Kuopio, Department of Physiology, Laboratory of Clothing Physiology, Kuopio, Finland ABSTRACT Intelligent garments can be used for monitoring body movements and also for monitoring vital functions, including heart rate and electrical muscle activity. In this paper we describe electromyographic (EMG) monitoring with textile-integrated electrodes. The aim was to clarify the usability and reliability of these EMG electrodes for different measurements. This study is part of the project called Methods and Models for Intelligent Garment Design. Healthy and fit subjects participated in treadmill or cycle ergometer tests and wore prototype tight-fitting shorts which contained textile-integrated EMG electrodes and integrated measuring equipment. For comparison, some subjects myoelectrical signals were recorded using traditional disposable bipolar surface EMG electrodes. The EMG measurement based on textile electrodes was also used in the field during various exercises. The usability of textile integrated EMG electrodes was an improvement over the traditional surface EMG method in dynamic work. Textile electrodes stayed in place despite motion and sweating. The new method employed no loose cables. Textileintegrated EMG measurements are appropriate in situations where it is possible to use skin-tight clothes. With such a garment, it is possible to record EMG data during the user s daily routines. 1 INTRODUCTION New textile materials, miniaturization of electrical components and other recent technical developments have enabled the integration of wires and electronics into clothing. In electronic textiles, sensors and other components, such as simple processing elements, are integrated into the fabric [1]. Such electronic textiles, which are composed of conductive fibers and smart materials, including piezoresistive and piezoelectric polymers, are useful for different applications in human monitoring [2]. Garments made of such textiles can be used for monitoring body movements and postures [3, 4], and also for monitoring vital functions [5], including e.g. heart rate and skin temperatures. Intelligent garments can also be used for measuring electrical muscle activity (Figure 1).

Figure 1. A prototype of an intelligent garment, which measures muscle activity (Mega Electronics Ltd, Kuopio, Finland). In this paper we introduce in detail electromyographic (EMG) monitoring with an intelligent garment. EMG is a versatile method to measure the function of different muscles. Surface EMG is used to quantify the level of activation of working muscles. [6] It can be used to estimate muscle fatigue noninvasively [7, 8] and it also provides a useful method to assess work-load in ergonomics [9]. In this on-going study, the usability and reliability of textile integrated EMG electrodes were clarified using various measurements and compared with the traditional way to measure surface EMG. In developing new measuring methods and systems, such as intelligent garments, it is important to determine the functionality and feasibility of these methods. Users experiences are also significant. In the present study, we collaborated with Mega Electronics Ltd, which has specialized in biosignal monitoring. This study is part of the project called Methods and Models for Intelligent Garment Design (MeMoGa), which focuses on the acceptability and usability of wearable intelligence. 2 SUBJECTS AND METHODS The subjects in the study were healthy and fit, and aged between 17-48 years old. All subjects were males. Each of them was asked to give written consent to the experimental protocol. The local research ethics committee approved the study. In the laboratory measurements, subjects (n=10) wore prototype tight-fitting shorts containing textile-integrated EMG electrodes and integrated measuring equipment (Figure 2). There was a wireless communication link, like WLAN or Bluetooth, in place between the measurement equipment and the software for data analysis in the personal computer (Figure 3). For the sake of comparison, we also recorded eight subjects myoelectrical signals using traditional disposable bipolar EMG electrodes (Figure 2). Subjects participated in treadmill or cycle ergometer tests. During the tests, EMG and respiratory

gas exchange data, blood lactate and heart rate were recorded. Treadmill tests were videotaped in order to analyse fatigue. This method of EMG measurement based on textile electrodes was also tested in the field condition during various exercises with one female. She also used both textile electrodes and traditional electrodes in isometric and isokinetic measurements and cycle ergometer tests. Figure 2. A traditional way to measure EMG: disposable electrodes with a measurement unit and an intelligent garment used in EMG measurements. Wireless communication (WLAN) ME6000 Biomonitor Software for data analyze Figure 3. An example of a measurement system based on an intelligent garment.

3 RESULTS The usability of textile integrated EMG electrodes turned out to be better than with the traditional surface EMG method in dynamic work, because the textile electrodes stayed in place despite motion and sweating. The prototype intelligent garment was easy and quick to put on and easy to use. There were no loose cables in the new system. The wires were integrated into the textile. This is a very important aspect in long-term measurements because signal artefacts resulting from many wires were decreased, and in this case the measurement data were clearer and more reliable. Figure 4 shows one subject s EMG data measured using textile-integrated electrodes during the treadmill test. The subject ran at increasing velocities from 8 to 16 km/h for 3 minutes at every velocity. There were short breaks between the different velocities. Measurements using textile electrodes have also shown good repeatability in field conditions. The intelligent garment was comfortable to use in different exercises. Measured data was useful to the user, because she got important information about the function of her muscles. Measured EMG data matched with user subjective experiences. Total physical load 1600 Momentary EMG (sum of four muscle groups) Averaged EMG (sum of four muscle groups) Velocity (km/h) 1400 36 1200 31 Muscle activity (uv) 1000 800 600 400 26 21 16 200 0 0:00:00 0:07:17 0:14:34 0:21:51 Velocity (km/h) 11 6 Figure 4. An example of one subject s recording at a treadmill test with increased workload (EMG data measured using textile integrated electrodes). 4 DISCUSSION Textile-integrated EMG measurements are appropriate in situations where it is possible to use skin-tight clothing. The method described based on an intelligent garment is more feasible compared to the traditional method of measuring muscle activity, especially in dynamic work,

because it is easier to use for everyone. It can be used everywhere and in almost every situation. The intelligent garment is nearly as light as a traditional piece of clothing. The traditional method of measuring EMG is useful in static measurements, and is a feasible method especially in laboratory circumstances. However, with an intelligent garment it is possible to record EMG data during the user s daily routines. The measurement with an intelligent garment does not disturb the user at all. This method can be exploited in sport activities and during rehabilitation after a trauma. There are also a number of suitable applications in ergonomics. For instance, it is possible to measure the activity of a user s back and upper limbs in order to estimate static tension during computer work. Intelligent garments which measure muscle activity can monitor workload individually. In the future, these garments will be able to teach workers how to use their muscles properly by giving feedback about muscle functions. With such a garment it is possible to prevent muscle overload. 5 CONCLUSIONS In all likelihood, intelligent garments including EMG measuring clothes will be as common in the future as traditional pieces of clothing are now. Intelligent garments can enhance the safety and well-being of the users. They can be a future solution to support health care. ACKNOWLEDGEMENTS We thank the Academy of Finland for the financial support for our intelligent garment research through the Proactive Computing programme and Mega Electronics Ltd for their cooperation. We also thank the whole consortium of the MeMoGa research project. REFERENCES 1 Martin T, Jones M, Edmison J, Shenoy R. Towards a design framework for wearable electronic textiles. Proceedings of the Seventh International Symposium on Wearable Computers, 2003, 190-9. 2 Paradiso R, Loriga G, Taccini N. Wearable system for vital signs monitoring. Stud Health Technol Inform 2004; 108: 253-9. 3 Martin T, Lockhart T, Jones M, Edmison J. Electronic textiles for in situ biomechanical measurements. 24 th Army Science Conference, 2004. 4 De Rossi, Carpi F, Lorussi F, Mazzoldi A, Scilingo EP, Tognetti A. Electroactive fabrics for distributed, conformable and interactive systems. The first IEEE International Conference on Sensors, 2002. 5 Lymberis A, Olsson S. Intelligent biomedical clothing for personal health and disease management: state of the art and future vision. Telemed J E Health 2003; 4: 379-86. 6 McArdle WD, Katch FI, Katch VL: Electromyography during maximal ballistic muscle actions. In Exercise physiology: energy, nutrition, and human performance. Philadelphia: Lippincott Williams & Wilkins. 2001: 527-9.

7 Kumar DK, Pah ND, Bradley A. Wavelet analysis of surface electromyography to determine muscle fatigue. IEEE Trans Neural Syst Rehabil Eng 2003; 4: 400-6. 8 Giannesini B, Cozzone PJ, Bendahan D. Non-invasive investigations of muscular fatigue: metabolic and electromyographic components. Biochimie 2003; 9: 873-83. 9 Hagg GM, Luttmann A, Jager M. Methodologies for evaluating electromyographic field data in ergonomics. J Electromyogr Kineol 2000; 5: 301-12.