Sensing fabrics for monitoring physiological and biomechanical variables: e-textile solutions

In the last few years, monitoringsystems based on multifunctional instrumented garments are playing an innovativerole in the development of more human oriented monitoring devices. Smartfabrics allow the monitoring of patients over extended period, in a naturalcontest, in biomedicine, as well as in several health-focused disciplines, suchas bio-monitoring, rehabilitation, telemedicine, tele-assistance, ergonomicsand sport medicine [1]. The innovation in this field is originated by thedevelopment of a new generation of textile sensors, combining electronics and informaticsnovelties, leading to the integration of multiple, smart functions intotextiles based sensing interfaces, aiming to the reduction of any impediment[2].

In this work, it will be report theexperiences gained during the last five years in the manufacturing of sensing systemsand their evolution in time. The wearable instrumented garments are based onconductive and piezoresistive fabric developed to work as textile sensors, wherethe mechanical and thermal properties are kept as those of textile materials.

Our research exploited differenttechnologies from flat and circular knitting to woven process, as well as theuse of a cut and sew approach to manufacture sensing elastic fabric on whichpiezoresistive sensors are printed, according to an engineered body map.

II. MATERIALS AND METHODS

A common textile process likeflat-knitting technology (Steiger SA4, Switzerland) allows the implementationof fabric where defined yarns are confined into insulated domains, realizing multi-layeredstructures where the conductive surface is sandwiched between two insulatedstandard textile surfaces.

Sensors, electrodes and connectionscan be fully integrated in the fabric and produced in one single step, by combiningconductive and non conductive yarns. The electrical properties of fabric aredue to the interaction among the fibres inside the yarn and the interactionamong the single loops inside the fabric. The whole textile structure has to beconsidered as a complicate array of electrical impedances [3].

Most sensors that are used for thedetection of vital signs and users movements need to be in close contact withthe body (like a second skin). The use of seamless knitting dedicated machine(i.e. Santoni SpA5) can provide elastic, adherent, comfortable garments withthese inherent properties.

A. Fabric Electrodes realized byflat-knitting technology

The conductive fabric electrodes,used in the frame of Wealthy European project (IST-2001-37778), have been knittedby means of flat knitting machine (Steiger SA4, Switzerland). They have beenrealized with commercial stainless steel threads twisted around a standardcontinuous viscose (or cotton) textile yarn [4].

The quality of bioelectrical signalsgathered in dynamic condition can be improved by coupling fabric electrodes witha hydrogel membrane, purchased by ST&D Ltd (Belfast, U.K.). The membrane reduces the contact resistance between the skin and the electrode, and increasesthe stability of the contact with its adhesive properties, without affectingthe comfort. The pH of the chosen membrane avoids skin irritation.

B. Fabric Electrodes realized by seamless knitting technology

Seamless sensorized garment have been processed with Santoni knitting machines, using stainless steel yarns produced by Bekintex to realize the electrodes and the Meryl Skin life purchased by Nylstar as basal yarn. Garments with different level of complexity, in term of sensors distribution, have been developed in the frame of the European project MyHeart (IST-2002-507816).

Seamless electrodes have been tested and used without the hydrogel membrane as the goal of the project was to interface the sensors directly with the skin.

C. Acquisition of Bioelectrical Signals through Fabric Electrodes

Fabric electrodes realized by flat-knitting machinery have been used to monitor Electrocardiogram (ECG), see Fig. 1, and respiratory activity by means of Impendence Pneumography (IP). IP has been described in previous authors work [5].

Fig. 1: Fabric electrodes realized by flat-knitting machinery. Circled ones are for ECG acquisition.

ECG signals have been acquired by using an acquisition card (National Instruments PCI-6036E). Signals have been conditioned by means of GRASS TELEFACTOR model 15LT device, with gain set to 1000.

A shirt has been realized by seamless machine in order to gather ECG and IP signal see Fig. 2.

Fig. 2: Fabric electrodes realized by seamless knitting technology: electrode positions for ECG acquisition.

Signals from the seamless system have been conditioned by using a device developed by CSEM (www.csem.ch) and developed within the WEALTHY project.

To improve the electrical signal quality in dynamic conditions, the electrodes have been wet.

D. Knitted Piezoresistive Fabric realized by seamless knitting technology

Piezoresistive fabric sensors have been realized with Santoni seamless machines using intarsia technique. The used conductive yarn (Belltron􀂓9R1 is produced by Kanebo Ltd, and it is coupled with an elastomer (Lycra).

E. Printed Piezoresistive Fabric realized by serigraphy technology

Coated fabric sensors have been realized with a conductive silicone, not designed for application in textile field. The viscosity of this material has been reduced to allow the use of an industrial coating process. Print screening technology has been evaluated as textile approach to coat the elastic substrate with the conductive elastomer. This approach allows to print on the fabric, the desired sensors topography as well as to solve the connection issue by using the same materials for both the functions: sensorial and circuital.

F. Mechanical characterization of Fabric Strain Sensors

In order to investigate the properties of piezoresistive fabric sensors, a protocol of mechanical characterization has been implemented. The fabric strain sensors have been subjected to predetermined mechanical stimuli imposed by a PC controlled system. Corresponding variations of electrical resistance have been collected through voltage divider, gathered by an acquisition card (National Instruments PCIMIO- 16E-4)) with sampling rate of 64 Hz.

Several samples of strain sensors have been subjected to different uniaxial mechanical stimuli following signals such as step and trapezium, both of them with variable strain amplitudes, and sinusoidal cycles with variable strain amplitudes at selected frequencies. Uniaxial mechanical stimuli have been applied along the length of both kinds of piezoresistive sensors.

The mechanical characterization aims to study the electrical response of fabric strain sensor as a function of the external mechanical stimuli.

G. Acquisition of Biomechanical Signals through Fabric Strain Sensors

Fig. 3: Knitted system for the acquisition of abdominal and thoracic respiratory activity

In order to evaluate the performances of knitted piezoresistive fabric sensors for biomechanical monitoring, the knitted piezoresistive sensors have been tested to detect both the respiration signal as a function of thorax movement and the elbow bends. A seamless t-shirt with fabric strain sensors has been realised respiratory signal, see Fig. 3.

Strain fabric sensors signals have been acquired using a voltage divider to convert resistance to voltage, gathered by an acquisition card (National Instruments PCI 6036) with sampling rate of 1000 Hz.

The respiration signals acquired with textile sensors have been compared with a respiratory effort transducer; model SSL5B, contained in the BIOPAC MP30 system.

The knitted piezoresistive fabric sensors are sensitive to changes in thoracic or abdominal circumference that occur during the respiratory activity.

The elbow bends signal detected by knitted piezoresistive fabric sensors has been compared with a commercial movement tracking system (electrogoniometer by Biometric).

The piezoresistive sensors performances allow the detection of movement index, while the printed piezoresistive sensors showed to be more efficient in the realisation of wearable kinaesthetic systems for gesture and posture monitoring [6],[7].

III. RESULTS AND DISCUSSION

A. Electrocardiogram detected by fabric electrodes

The wearable system realized by flat-knitting technology, showed in Fig. 1, is able to acquire simultaneously five ECG leads. An example of signals detected is reported in Fig. 4.

Fig. 4: Detail of ECG signal in basal condition detected by using fabric electrodes realized by flat-knitting technology

Similar results have been obtained by detecting ECG signals with the seamless garment, see Fig. 5.

A more accurate analysis of system performances has been reported on previous publication [8], [4].

Fig. 5: Detail of ECG signal in basal condition detected by using fabric electrodes realized by a seamless-knitting technology

B. Characterization of piezoresistive fabric sensors

The electrical resistance variation of strain fabric sensors due to mechanical deformation has been studied.

The change in resistance is correlated with the change in strain amplitude. The piezoresistive behaviour of knitted of piezoresistive fabric sensors is mainly due to the change of conductive contacts during the local deformation of textile structure. This mechanical deformation modifies the charges path, not only for the different interaction among the single filaments inside the yarn, but also for the deformation of the knitted fabric loops during the stretching and relaxing phase

[3]. A yarn is a very complex structure where several filaments or fibers are twisted together, the resulting fabric is a network where the contacts among the single filaments are random.

Fig. 6: Trapezoidal wave input versus time (upper) and corresponding electrical response of knitted piezoresistive fabric sensor versus time (lower)

Results have shown that applying a trapezoidal wave as mechanical input (see Fig. 6), the electrical resistance value increases up to a certain value, and then it decreases to a steady-state value. This relaxing time is too long to make fabric sensors suitable for monitoring real time human body movements. When a decreasing input is applied, the electrical resistance shows a little positive peak before decreasing to the settling value.

In order to face the problem related to the non-linearity showed in Fig. 6, with the aim of using the fabric sensors in realm time, that requires a correction of sensor delay, a model have been formulated in [6].

In Fig. 7 the knitted piezoresistive sensor response has been compared to the signal obtained with Biopac pneumograph in order to monitor the respiratory activity, both the signals have been acquired simultaneously.

Fig. 7: Signal derived by KPF sensor (upper) and Biopac pneumograph (lower) during normal respiration.

Fig. 8 shows the comparison between the knitted piezoresistive sensor signal during elbow bends, and the response obtained through an electrogoniometer by Biometric􀂓; both the signals have been acquired simultaneously.

Fig. 8: Signal derived by knitted piezoresistive fabric sensor (upper) and Electrogoniometer (lower) during fast elbow bends.

Printed piezoresistive fabric sensors exhibit a similar electrical behavior and they have been characterized in previous works, [6] [7].

The realization of a garment devoted to the analysis of human movements is an application of printed piezoresistive fabric, an example is showed in Fig. 9.

Fig. 9: Examples of garments for biomechanical monitoring.

From design and manufacturing perspective, a special process has been set up to realize biomechanical monitoring garments, where sensors and connections are realized with the same conductive materials. This choice has been adopted in order to solve a critical issue related to the connectivity between the coated strain sensors and the electronics, keeping the elasticity and wearability of garment. For this reason printing and cabling was realized before the cut and sew phase, by using a hybrid solution: coating on the sewing done with conductive flexible yarns that are used as conductive cables.

IV. CONCLUSION

In this work a description of novel sensors developed to be integrated in sensorised garments for monitoring vital signs and body gesture/posture has been presented. The main advantage ensured by these systems is the possibility of wearing them for a long period of time without discomfort. Several issues deriving from the employment of the new technology which has consented the realization of these unobtrusive devices have been addressed. Moreover, it has been pointed out the use of these sensorised garments as a valid alternative to existing instrumentation applicable in several health care areas. Finally, results on the performances of the sensing systems were briefly reported. The work continues toward potential commercial exploitation.

REFERENCES

1. Wearable eHealth Systems for Personalised Health Management - State of the Art and Future Challenges, Volume 108 Studies in Health Technology and Informatics 2004, Edited by: A. Lymberis and D. De Rossi, IOS Press, Amsterdam, 2004.

2. IEEE TRANSACTION on INFORMATION TECHNOLOGY IN BIOMEDICINE, SPECIAL SECTION ON NEW GENERATION OF SMART WEARABLE HEALTH SYSTEMS AND APPLICATIONS, vol.9, no.3. SEPT. 2005, Edited by: A. Lymberis and D. De Rossi.

3. R. Wijesiriwardana, T .Dias, S. Mukhopadhyay, Resistive fibremeshed transducers. Proceedings of the Seventh IEEE International Symposium of Wearable Computers, 21-23 Oct. 2003 Piscataway, NJ, USA, 200-209

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6. F. Lorussi, W. Rocchia, E. P. Scilingo, A. Tognetti, and D. De Rossi, Wearable redundant fabric-based sensors arrays for reconstruction of body segment posture, IEEE Sensors Journal, vol. 4, no. 6, pp. 807818, December 2004

7. Tognetti, F. Lorussi, R. Bartalesi, S. Quaglini, M. Tesconi, G. Zupone, and D. De Rossi, Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation, Journal of NeuroEngineering and Rehabilitation, vol. 2, no. 8, March 2005.

8. E.P.Scilingo, A. Gemignani, R.Paradiso, N. Taccini, B. Ghelarducci and D. De Rossi, Sensing Fabrics for Monitoring Physiological and Biomedical Variables, IEEE Transaction On Information Technology In Biomedicine, Special Section On New Generation Of Smart Wearable Health Systems And Applications, vol.9, no.3. (pp 345- 352), SEPTEMBER 2005.

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