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Gait analysis aims to study human motion and its potential association with chronic diseases, such as Parkinson's disease and hemiplegic paralysis, by extracting various gait characteristics. It has been a challenging problem to accurately extract temporal and spatial gait parameter and to explore the relationship between gait signal and a disease of interest. In this study, we introduce a gait sensing...
As our population ages, neurological impairments and degeneration of the musculoskeletal system yield gait abnormalities, which can significantly reduce quality of life. Gait rehabilitative therapy has been widely adopted to help patients maximize community participation and living independence. To further improve the precision and efficiency of rehabilitative therapy, more objective methods need...
Monitoring people during their daily activities has become a topic of great interest among the scientific community, largely due to the great advances in microelectronics, wearable devices, ubiquitous computing, or artificial intelligence. Among these advances, smartphones have arisen as a key technology to monitor people, thanks to their onboard sensors and their increasing computational capabilities...
In this paper, we present an approach for person identification using morphing footsteps measured from a fabric-based pressure mapping sensor system. The flexible fabric sensor is 0.5 mm thin and operates under a 5 mm thick normal carpet; therefore, it can be easily implemented into modern smart living spaces. We extract features concerning single steps with the shifting of gravity center, maximum...
Human gait is cyclic process, which is affected by various neurological disorders like Parkinson's disease (PD) or multiple sclerosis (MS). Instrumented gait analysis facilitate monitoring and diagnosing motor deficiencies; it may serve as a tool for clinicians evaluating the patients. This study aims at finding biomechanical parameters that allow separating pathological gaits via application of inertial...
As sensor-rich mobile devices became a commodity, more opportunities appeared for the creation of location-aware services. While GPS is a well established solution for outdoor localization, there is still no standard solution for localization indoors. This paper presents a novel accurate indoor positioning mechanism that is meant to run in common smartphones to be a readily and widely available solution...
Smart living and well aging represent key challenges for our society. The precursor state of adverse outcomes that characterize aging has been recognized from scientific community with the frailty syndrome, determined by the loss of physical and psychological capacities. In this paper we define gait and posture indexes that can be effectively and unobtrusively measured using computer vision and RGBD...
This paper proposes a fatigue level estimation method using mat type load distribution sensor. Fatigue level indicates human condition of daily living. And estimated fatigue level is used for notification and suggestion by robot partner through informationally structured space. The sensor measures sole pressure distribution. To analysis the gait, gait speed, step duration, balance abilities and forces...
This article describes a method for differentiating two types of horse gaits: walk and trot. Recognition of gait types is significant for different research branches. It is important in animal behavior analysis, gait and stride timing analysis, lameness detection, sports such as horse trotting and identifying opportunities for the use of horses. Research described in this article concerns detection...
Gait disorders are a primary consequence of Parkinson's Disease (PD), resulting in loss of patients' independence. Recently, Rhythmical Auditory Stimulation (RAS) gave a preliminary proof to benefit gait quality, but the specific methodology requires a long walkway, preventing the use of a traditional complete gait analysis. In the present work we describe an unobtrusive, wearable setup and the related...
With the recent development of wireless and sensing technology, wireless sensor devices have invaded the medical area with a wide range of capability. These devices allow medical practitioners to monitor the patients remotely and timely. However, it is known that the body movement can result in significant fluctuations of the radio signal, affecting the data communication. Real-time activity recognition...
Communication between nodes in Wireless Sensor Networks (WSNs) can be interrupted by body movement. With the demand of the use of WSNs in health monitoring systems, it is necessary to investigate and provide a solution to overcome the interference caused by human body parts. The body parts such as the elbow and knee can reflect, absorb or obstruct the radio signal that can disrupt the radio communication...
Human gait is a complex motion that implies the movement of different parts of the body such as arms, legs and feet, being the functional human movements' analysis indispensable for bio-mechanical diagnostic and treatment tool for clinics and rehabilitation services. During the rehabilitation process, walkers are frequently prescribed to improve the patient's stability but can also be transformed...
In this work a prototype video-based system for assessing the state of patients with Multiple sclerosis is proposed. In particular we introduce an automated system for capturing and analyzing gait sequences from patients performing the well known 2-minute walking test. The contribution of this work is twofold. First we provide a computerized approach for performing the 2-minute walk test and showing...
Ability to walk plays an important role in human daily activities. During walking, the pressure pattern of the sole of the foot contains valuable information about the anatomic and physiologic situation of the body. Plantar pressure measurement systems can provide this information for scientists. In this paper, a device developed to measure plantar pressure and wirelessly transmit the data to a host...
Gait analysis is considered as an important process which has been wildly adopted in many clinical applications to identify and quantify the lower body functioning impairment of hémiplégie patients. On contrary to the traditional measures which were based on manual observation, numerous researches in recent years have been carried out on utilizing modern assistive devices to analyze gait pattern and...
Gait parameters such as step and stride lengths, step and stride times, and time spent in single and double support are important factors for physicians to diagnose and/or monitor patients. Typically, assessing these spatial and temporal parameters accurately require an expensive equipment, which cannot be afforded by most general hospitals in developing countries. This paper presents a light-weight...
This paper presents a framework of gait analysis for children with cerebral palsy (CP) using electromyography (EMG) and acceleration (ACC) signals. In this framework, ACC signals are firstly processed for stride cycle detection and segmentation, and then utilized to reveal kinematic information associated with gait abnormality, whereas the EMG signals are adopted to assess abnormal muscle activation...
The need for more security on mobile devices is increasing with new functionalities and features made available. To improve the device security we propose gait recognition as a protection mechanism. Unlike previous work on gait recognition, which was based on the use of video sources, floor sensors or dedicated high-grade accelerometers, this paper reports the performance when the data is collected...
This paper presents machine learning (ML) techniques for development of a control scheme to be used in functional electrical stimulation (FES) of hemiplegic walking. The goal is to make an electrical stimulation pattern by mapping the sensors signals acquired during walking (input) to activities of muscles (output) acting around knee and ankle joints. Two machine learning techniques with ability of...
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