Gait Analysis for Fall Prediction Using Hierarchical Textile-Based Capacitive Sensor Arrays

Abstract

Falls are a major cause of injuries in adults above the age of sixty-five. The economic aftermath of falls and their consequent hospitalization can be huge, totaling more than 30 billion dollars in 2010 alone. A plausible way of mitigating this problem is accurate prediction of future falls and taking proactive remedial action. Spatio-temporal variation in gait is a reliable indicator of a future fall, however, existing systems focus on gait analysis in clinical settings and are not tuned towards continuous gait analysis. In this paper, we present the design of a novel textile capacitive sensor array-based system built into clothing that can reliably capture spatio-temporal gait attributes in a home setting.A key novel research contribution of our work is a context-aware hierarchical signal processing architecture that breaks down the signal processing algorithm into a hierarchy of processing elements. The lower power processing components perform generic feature extraction using observations derived from the capacitor plates, while the higher-level processors aggregate features to infer gait attributes such as stride speed and inter-leg spacing. The system activates the higher power processing elements only when it detects walking. We have prototyped our system using textile capacitive plates built into an ace-bandage and a custom FPGA-based system and show that our system can accurately detect gait attributes that have high correlation with falls, while consuming minimal energy as estimated for a multi-clock-domain 180-nm IC.Research Contributions: The design, implementation, and evaluation of our prototype system presents three novel research contributions.(a) Wearable textile-based capacitive sensor arrays (CSAs) for gait analysis: We present the use of flexible

Estimation of Ankle Joint Power During Walking Using Two Inertial Sensors

“…Studying the gait parameters, such as speed, step length, cadence, gait phases, and step variation [1,2], can help analyze performance and efficiency in sports activities, such as running [3], and is also a useful tool for understanding the gait abnormalities that might occur because of neurological, orthopedic, or medical conditions [4]. Clinical monitoring of gait is one of the common methods to diagnose and characterize disorders that might lead to falls and subsequent injuries [5,6,7,8,9]. Among various gait parameters, ankle joint power, as an indicator of the ability to control lower limbs, is of great relevance in clinical applications.…”

A Wearable Gait Phase Detection System Based on Force Myography Techniques

“…Walking is one of the basic activities of humans in everyday life and gait analysis provides a systematic and quantitative means to assess human locomotion [ 1 , 2 ]. Gait analysis has a wide range of applications spanning from sports performance analysis [ 3 ] to fall detection [ 4 ] and clinical monitoring of gait [ 5 , 6 , 7 , 8 ]. The sequences for walking are interpreted as gait cycles and are characterized by two main phases: the stance phase and the swing phase.…”

Finding Common Ground

“…The integration of capacitive touch sensors into clothing was first explored in 1998 [143]. Researchers have since used this approach to implement health applications [8,30,185] and ubiquitous touch interfaces [43,76,92,143,152]. Sensors have thereby been placed on pants [172,185], belts [43,196], shoes [145], gloves [104,209], and jackets [152].…”

“…For example, capacitive sensing can be enabled on printed objects by filling tubes inside the objects with conductive inks [174], interrupting the print process to integrate electronics [181] or combining conductive and non-conductive print materials [20,123,177]. Conductive yarns and fabrics open new possibilities for flexible electrode design, e.g., the integration into clothing [8,30,92,152,185]. Conductive paint has also been applied to retrofit existing clothing with sensing capabilities [76,200].…”

“…Flexible and stretchable interfaces enable new types of interaction [60,77] and support ubiquitous deployments, e.g., in fabric and clothing [8,30,152,185] or directly on the human body [98,103,217]. …”