Guido Gioberto

Detecting bends and fabric folds using stitched sensors

In this paper we describe a novel method for detecting bends and folds in fabric structures. Bending and folding can be used to detect human joint angles directly, or to detect possible errors in the signals of other joint-movement sensors due to fabric folding. Detection is achieved through measuring changes in the resistance of a complex stitch, formed by an industrial coverstitch machine using an un-insulated conductive yarn, on the surface of the fabric. We evaluate self-intersecting folds which cause short-circuits in the sensor, creating a quasi-binary resistance response, and non-contact bends, which deform the stitch structure and result in a more linear response. Folds and bends created by human movement were measured on the dorsal and lateral knee of both a robotic mannequin and a human. Preliminary results are promising. Both dorsal and lateral stitches showed repeatable characteristics during testing on a mechanical mannequin and a human.

Theory and characterization of a top-thread coverstitched stretch sensor

One of the chief challenges of wearable sensing is adapting electronic components and sensors to the wearable environment. Electronic components are often rigid, bulky, and impermeable: factors that usually detract from wearing comfort. Here, we present a novel stretch sensor fabricated using the top thread of a standard industrial coverstitch machine. The machine is common in apparel production and offers the ability to easily fabricate custom-placed stretch sensors on textile and apparel products. The sensing properties of the stitch are enabled by a conductive thread which increases its electric resistance as the fabric is stretched, due to the geometry of the stitches. Our empirical analysis shows a sensor response in the order of 10 ohms, with almost linear behavior prior to saturation (when the stitch is fully stretched) for low-frequency extensions of 119% of initial sample length. An equivalent electrical model is presented for theoretical modeling of the sensor behavior.

Garment Positioning and Drift in Garment-Integrated Wearable Sensing

Perceptibility on the part of the user is a key influence on the success or failure of a wearable sensor. Most wearable sensors seek to measure or monitor parameters of the body as accurately as possible, yet wearable sensors are notoriously plagued by the error (also referred as noise) that may be introduced by the movement of the sensor over the body surface. In this paper, we implement a novel method for analyzing error introduced by garment properties in garment-integrated wearable sensing during body movement, and assess in detail the errors introduced by donning and doffing of a garment (garment positioning error) and by garment drift during the gait cycle (drift error).

Measuring movement of denim trousers for garment-integrated sensing applications

The movement of everyday garments over the body surface during wearing often presents a problematic source of noise or error for garment-integrated wearable sensors. This paper describes early results of an assessment of the impact of body location and garment ease on movement of the garment over the body surface. The method implemented uses a running mannequin with a repeatable gait cycle as the source of humanoid motion, and measures the movement of a set of custom-graded denim trousers in 5 ease amounts over the mannequins surface during the gait cycle. Initial results show consistent patterns of displacement over the body surface.

Washability of e-textile stretch sensors and sensor insulation

An effective way to monitor body movements and positions (including physiological signals like breathing) without causing discomfort is through integration of sensors and electronics into base layers of clothing. However, for many applications (including sports and fitness), such sensors must be washable. Here, we present results of experiments evaluating the impact of washing on an e-textile stretch and bend sensor. Two cases are investigated: un-insulated sensors and sensors insulated with a fusible polymer film. Results show small-scale drift in the un-insulated sensor, which is magnified by machine washing and further by machine drying. Similar results are observed in delamination effects for the insulating film.

Lower-limb goniometry using stitched sensors: effects of manufacturing and wear variables

Smart fabrics allow for convenient wearable sensing solutions to monitor body movements during our daily life. However, garment-integrated sensing presents challenges for accurate sensing, due many variables including those presented by variability in garment and sensor dimensions due to cut-and-sew manufacturing processes, and those introduced by re-positioning of integrated sensors when the garment is donned and doffed. Here, we measure the effect of variability in garment positioning due to donning and doffing, garment dimension due to manufacturing tolerances, and sensor dimension due to manufacturing defects on the accuracy of a stitched goniometer used to measure flexion of the knee and hip. Results show that variability in garment positioning and garment dimension have a minimal effect on sensor accuracy, but sensor dimensions have a more significant influence on accuracy.

Measuring joint movement through garment-integrated wearable sensing

Garment-Integrated body sensing is an alternative approach to sense body movements in wearable sensing. Textile-integrated sensors have the potential to equip everyday clothes with smart capabilities, making the detection of body movements accessible during normal life activities. The practicality of this solution preserves variables directly related to the wearers needs such as Comfort, Perceptibility, and Awareness that must be prioritized equally with Accuracy and Precision of the sensor data. The central contribution of this approach is to improve the quality of the measured data while preserving user comfort.

Garment-integrated wearable sensing for knee joint monitoring

Body monitoring is one of the most intuitive and direct applications for technologies that are wearable. Wearable devices are capable of detecting body movements using wearable sensors, and using signals to capture anomalies as well as good patterns in our daily activities. Clothes provide the most accessible platform for embedding sensors and electronic components, preserving imperceptibility and user comfort, especially for long term body monitoring applications. Both perceptibility and comfort variables are associated with the willingness of the user to wear the device and with the quality of the data captured (that should reflect the unbiased wearer activity as if the user would not be wearing any device).