| Literature DB >> 27240361 |
Giuseppe Andreoni1, Carlo Emilio Standoli2, Paolo Perego3.
Abstract
Designing smart garments has strong interdisciplinary implications, specifically related to user and technical requirements, but also because of the very different applications they have: medicine, sport and fitness, lifestyle monitoring, workplace and job conditions analysis, etc. This paper aims to discuss some user, textile, and technical issues to be faced in sensorized clothes development. In relation to the user, the main requirements are anthropometric, gender-related, and aesthetical. In terms of these requirements, the user's age, the target application, and fashion trends cannot be ignored, because they determine the compliance with the wearable system. Regarding textile requirements, functional factors-also influencing user comfort-are elasticity and washability, while more technical properties are the stability of the chemical agents' effects for preserving the sensors' efficacy and reliability, and assuring the proper duration of the product for the complete life cycle. From the technical side, the physiological issues are the most important: skin conductance, tolerance, irritation, and the effect of sweat and perspiration are key factors for reliable sensing. Other technical features such as battery size and duration, and the form factor of the sensor collector, should be considered, as they affect aesthetical requirements, which have proven to be crucial, as well as comfort and wearability.Entities:
Keywords: ergonomics; human factors; sensor design; sensorized clothes; smart textiles; textile sensors; wearable systems
Year: 2016 PMID: 27240361 PMCID: PMC4934195 DOI: 10.3390/s16060769
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.576
Figure 1The comparison of the two generations of Wearable Health Systems (WHS). (a) Wearables 1.0: the garments and other accessories are the supporting platform of a set of devices for monitoring human functions; (b) Wearables 2.0: sensors and related electronics components and integrated into the garments (adapted from [5]).
The basic signals and the derived parameters to be measured by wearable sensing systems, and the identification of the sensor to be used and its possible typologies. ECG: Electro-Cardio-Gram, EMG: Electro-Myo-Gram, EEG: Electro-Encephalo-Gram.
| No. | Signal 1 | Parameter (s) | Sensor | Typology |
|---|---|---|---|---|
| 1 | ECG | Electrical heart activity, Heart Rate | electrode | Adhesive, textile, plate |
| 2 | EEG | Electrical Brain activity | electrode | Plate, textile prototypes |
| 3 | EMG | Electrical muscle activity | electrode | Adhesive, textile prototypes |
| 4 | Respiration | Breathing rate, Volumes, respiratory times | Strain gauge; Electrode for impedance measure | Hardware probe, adhesive, textile sensor |
| 5 | Blood gas | SpO2, CO2, Heart rate | LED/optical | Hardware probe, POF for signal transmission |
| 6 | Blood pressure | Systolic/diastolic values, Heart rate | Cuff | Hardware System |
| 7 | Interface pressure | Contact pressure | Piezoresistive; capacitive | Piezoresistive ink, capacitive sensor both electric and textile |
| 8 | Resistance | GSR, Body impedance | Electrodes for Impedance measure | Hardware System |
| 9 | Temperature | Temperature | Piezoresistive | Hardware probe (thermistor) |
1 Note: Movement is measured with miniaturized hardware system applied to each body district.
Figure 2A simplified map of the bio-signals to be measured from the human body through wearables systems and the corresponding sensing point. ECG: Electro-Cardio-Gram, EMG: Electro-Myo-Gram, EEG: Electro-Encephalo-Gram.
Materials for textile electrodes and related properties.
| Material | Merits | Demerits |
|---|---|---|
| Conductive rubber | High conductivity, easy to shape, cheap | Poor flexibility and permeability to air and liquid |
| Silver-coated polymer foam | High conductivity, easy to shape, flexible, antibacterial | Poor washability and permeability to air and liquid, possible oxidation |
| Metal-coated or sputtered fabric | High conductivity, fabric material | Poor washability, possible oxidation |
| Woven metal fabric | Controlled conductivity, fabric material | Difficult to handle, skin irritation, low elasticity |
| Woven conductive polymer fabric | Fabric material, elasticity | Low conductivity |
| Carbon yarn | High mechanical resistance, high thermal insulation | Average conductivity, skin irritation, low elasticity |
| Stainless steel yarn | High conductivity, no skin interaction | Low elasticity, high weight |
Figure 3A model of capacitance sensor implemented with two layers of conductive fabric and a spacer that could be a 3D textile.
Figure 4A model of a textile strain gauge and the related description. (a) The modification of the yarn configuration inside the fabric while stretching it; a wider superficial contact area is obtained among the different conductive yarns, thus resulting in a decrease in the electrical resistance. (b) The typical graphical representation of the mathematical equation that expresses the relationship between elongation and electrical resistance of the textile strain gauge.
Figure 5An example of an application of textile strain gauges in the monitoring of respiratory acts and related parameters. (a) A sensorized T-shirt for monitoring respiration through textile strain gauges at thorax and abdominal level; (b) The comparison of the signals from the textile sensor and the pneumo-tachograph (gold standard technique); the blue line shows the gold standard data measured during normal breathing at resting in sitting posture, and the red line shows the textile strain gauge signal in the same condition. A ~5% air volume overestimation at peaks is shown.
Figure 6The electrode setup for measuring heart electrical activity. (a) The standard sensor positions for Electro-Cardio-Gram (ECG) measurements in the reduced five-lead configuration; (b) Transversal ECG sensors setup to avoid pectoralis muscles artifacts (C7 = in correspondence with the 7th cervical vertebra, XP = in correspondence of the xiphoid process).
Figure 7The effect of movement artifacts on bioelectrical signal recordings: an example of the different signal quality with the “standard” ECG lead implemented by two sensors on the left and right costal chest and in correspondence with the 10th rib (RL and LL in Figure 6). (a) 4 s of the typical ECG pattern recorded during quiet activity in sitting posture (typing). (b) A corrupted 4-s ECG signal with no recognizable peaks during upper limb movements (frontal abduction/adduction) in the same posture.
Figure 8A methodology and the corresponding decision tree for designing smart sensing garments.