Gabriele Dalle Mura

New generation of wearable goniometers for motion capture systems

BackgroundMonitoring joint angles through wearable systems enables human posture and gesture to be reconstructed as a support for physical rehabilitation both in clinics and at the patient’s home. A new generation of wearable goniometers based on knitted piezoresistive fabric (KPF) technology is presented.MethodsKPF single-and double-layer devices were designed and characterized under stretching and bending to work as strain sensors and goniometers. The theoretical working principle and the derived electromechanical model, previously proved for carbon elastomer sensors, were generalized to KPF. The devices were used to correlate angles and piezoresistive fabric behaviour, to highlight the differences in terms of performance between the single layer and the double layer sensors. A fast calibration procedure is also proposed.ResultsThe proposed device was tested both in static and dynamic conditions in comparison with standard electrogoniometers and inertial measurement units respectively. KPF goniometer capabilities in angle detection were experimentally proved and a discussion of the device measurement errors of is provided. The paper concludes with an analysis of sensor accuracy and hysteresis reduction in particular configurations.ConclusionsDouble layer KPF goniometers showed a promising performance in terms of angle measurements both in quasi-static and dynamic working mode for velocities typical of human movement. A further approach consisting of a combination of multiple sensors to increase accuracy via sensor fusion technique has been presented.

Exploiting Wearable Goniometer Technology for Motion Sensing Gloves

This paper presents an innovative wearable kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove is conceived to capture hand movement and gesture by using KPF in a double-layer configuration working as angular sensors (electrogoniometers). The sensing glove prototype is endowed by three KPF goniometers, used to track flexion and extension movement of metacarpophalangeal joint of thumb, index, and middle fingers. The glove is devoted to the continuous monitoring of patients during their daily-life activities, in particular for stroke survivors during their rehabilitation. The prototype performances have been evaluated in comparison with an optical tracking system considered as a gold standard both for relieving static and dynamic posture and gesture of the hand. The introduced prototype has shown very interesting figures of merit. The angular error, evaluated through the standard Bland Altman analysis, has been estimated in

Wearable biomonitoring system for stress management: A preliminary study on robust ECG signal processing

{\bf \pm 3^\circ}

Modulation of isochronous movements in a flexible environment: links between motion and auditory experience.

which is slightly less accurate than commercial electrogoniometers. Moreover, a new conceptual prototype design, preliminary evaluated within this study, is presented and discussed in order to solve actual limitations in terms of number and type of sensor connections, avoiding mechanical constraints given by metallic inextensible wires and improving user comfort.

Gait and Anthropometric Profile Biometrics: A Step Forward

There is a close correlation between stress and health risk factors such as poor immune function and cardiovascular problems. Various researches showed that long-term exposure to stress and its related diseases are responsible of dramatic increase of mortality in theWestern Countries. In this context, the European Collaborative Project INTERSTRESS is aimed at designing and developing advanced simulation and sensing technologies for the assessment and treatment of psychological stress, based on mobile biosensors. In this paper a wearable system able to implement the acquisition and the real-time elaboration of the ECG signal for stress management purposes will be described. A novel and robust algorithm for QRS complex detection has been developed. Robust QRS detection is fundamental to evaluate Heart Rate and Heart Rate Variability that are relevant parameters used as quantitative marker related to mental stress. In comparison to existing solutions the realized algorithm presents many advantages: an adaptive optimal filtering technique that avoids the use of thresholds and empirical rules for R peaks detection, low computational cost for real time elaboration and good tollerance with noisy ECG signal.

Event Related Biometrics: Towards an Unobtrusive Sensing Seat System for Continuous Human Authentication

The ability to perform isochronous movements while listening to a rhythmic auditory stimulus requires a flexible process that integrates timing information with movement. Here, we explored how non-temporal and temporal characteristics of an auditory stimulus (presence, interval occupancy, and tempo) affect motor performance. These characteristics were chosen on the basis of their ability to modulate the precision and accuracy of synchronized movements. Subjects have participated in sessions in which they performed sets of repeated isochronous wrist’s flexion–extensions under various conditions. The conditions were chosen on the basis of the defined characteristics. Kinematic parameters were evaluated during each session, and temporal parameters were analyzed. In order to study the effects of the auditory stimulus, we have minimized all other sensory information that could interfere with its perception or affect the performance of repeated isochronous movements. The present study shows that the distinct characteristics of an auditory stimulus significantly influence isochronous movements by altering their duration. Results provide evidence for an adaptable control of timing in the audio–motor coupling for isochronous movements. This flexibility would make plausible the use of different encoding strategies to adapt audio–motor coupling for specific tasks.

Isochronous sounds for isochronous movements: The multiplex control of timing in human subjects.

Emerging biometrics based on the measurements of body dynamic and static characteristics have gained increased importance in all the surveillance environments where the security is a mandatory priority. Some technology branches are involved to find unobtrusive solutions for authentication systems, where the human subject should not take care of the system itself so that he/she is free to perform his/her normal actions. In the first part of the chapter a novel gait recognition system is presented that introduces the use of range data for gait signal analysis. In the second part of the chapter, a description of system based on a sensing seat for event-related continuous authentication purpose in office and car scenarios is presented. Both biometric technologies introduce new means of verifying the user identity, by exploiting the analysis of common and every-day activities recorded in an unobtrusive manner and their recognition accuracy has been seen to be very high in the performed experiments.

WEARABLE MOTION CAPTURE DEVICES BASED ON SMART TEXTILE TECHNOLOGY

The present work is focused on the improvement of a Sensing Seat system previously developed by the authors for the initial authentication purpose in office and car scenarios. The goal is to obtain an event-related continuous authentication system, where the human subject should not take care of the system itself so that he is free to perform his normal actions. The system is realized by means of a sensing cover where conductive elastomers are used as strain sensors. The deformation of the cover caused by the body shape while actions are performed by the subject are used to obtain time-dependent relevant features. Such information are then analyzed by suitable classifiers that are able to perform the real-time continuous authentication task. A measurement campaign was carried out using data from 24 human subjects employed in an office scenario while a set of 22 actions were performed. The authentication capabilities of the system are reported in terms of acceptance and rejection rates, showing a high degree of correct classification.