4,144 research outputs found
Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations
Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions
On the Design and Development of a Zigbee-Based Multimodal Input-Output Monitoring-Actuating System
The monitoring of a physically challenged patient’s activities is a crucial and difficult task for the medical professionals. The design and development of a multimodal- input and output wireless system with two sensors and three actuators that can be used for just monitoring or for both monitoring and stimulating are discussed in this research. Touch and tilt sensors at the input part of the system attached to Zigbee modules communicate in a wireless manner with voice, vibration and light actuators connected to Zigbee modules at the output part. The hardware and the software parts are designed and integrated in such a way that a new sensor at the input or a new actuator at the output can be included or excluded based on the needs of the patient. It is shown how to design and develop sensors. In an application programming interface communication mode, 3 XBee series 1 modules send and receive data in a wireless manner. The prototype of the system was tested with promising results in the case of the patients with inattention disorder. This system can be used for monitoring the activities of a patient and also for actuating certain stimulus in the patient side in case of necessity
Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology
INE/AUTC 10.0
Real-time Assessment and Visual Feedback for Patient Rehabilitation Using Inertial Sensors
Rehabilitation exercises needs have been continuously increasing and have been projected to increase in future as well based on its demand for aging population, recovering from surgery, injury and illness and the living and working lifestyle of the people. This research aims to tackle one of the most critical issues faced by the exercise administers-Adherence or Non-Adherence to Home Exercise problems especially has been a significant issue resulting in extensive research on the psychological analysis of people involved. In this research, a solution is provided to increase the adherence of such programs through an automated real-time assessment with constant visual feedback providing a game like an environment and recording the same for analysis purposes. Inertial sensors like Accelerometer and Gyroscope has been used to implement a rule-based framework for human activity recognition for measuring the ankle joint angle. This system is also secure as it contains only the recordings of the data and the avatar that could be live fed or recorded for the treatment analysis purposes which could save time and cost. The results obtained after testing on four healthy human subjects shows that with proper implementation of rule parameters, good quality and quantity of the exercises can be assessed in real time
Comparing Dynamic Hand Rehabilitation Gestures in Leap Motion Using Multi dimensional Dynamic Time Warping
We propose and evaluate the use of Multi-dimensional Dynamic Time Warping (MDTW) for comparing dynamic hand rehabilitation gestures that would be performed by a patient (query) relative to hand gestures prepared by a physiotherapist (reference). MDTW enables us to determine how similar or different a query dynamic hand gesture is to a reference one whilst filtering out unwanted sources of error resulting from positional, rotational or speed differences between the query and the reference actions. It produces a minimum-distance value of a warp path after aligning a query dynamic hand gesture with a reference one. A low minimum-distance value implies the two gestures being compared are similar and high minimum-distance value implies the two gestures vary to a greater extent. When we deliberately compare a specific hand gesture with itself, we obtain a minimum-distance value of 0° indicating the similarity is 100%. Furthermore, when we compare two closely similar hand gestures i.e. gesture 1 and gesture 4, a minimum-distance value of 35.9° is obtained. However, when we compare two quite different gestures i.e. gesture 2 and gesture 3, a minimum-distance value of 248.5° is obtained. Therefore, a physiotherapist can establish whether a patient performs hand rehabilitation gestures satisfactorily or an adjustment is required based on the minimum-distance values of the warp paths
Smart Technology for Telerehabilitation: A Smart Device Inertial-sensing Method for Gait Analysis
The aim of this work was to develop and validate an iPod Touch (4th generation) as a potential ambulatory monitoring system for clinical and non-clinical gait analysis. This thesis comprises four interrelated studies, the first overviews the current available literature on wearable accelerometry-based technology (AT) able to assess mobility-related functional activities in subjects with neurological conditions in home and community settings. The second study focuses on the detection of time-accurate and robust gait features from a single inertial measurement unit (IMU) on the lower back, establishing a reference framework in the process. The third study presents a simple step length algorithm for straight-line walking and the fourth and final study addresses the accuracy of an iPod’s inertial-sensing capabilities, more specifically, the validity of an inertial-sensing method (integrated in an iPod) to obtain time-accurate vertical lower trunk displacement measures.
The systematic review revealed that present research primarily focuses on the development of accurate methods able to identify and distinguish different functional activities. While these are important aims, much of the conducted work remains in laboratory environments, with relatively little research moving from the “bench to the bedside.” This review only identified a few studies that explored AT’s potential outside of laboratory settings, indicating that clinical and real-world research significantly lags behind its engineering counterpart. In addition, AT methods are largely based on machine-learning algorithms that rely on a feature selection process. However, extracted features depend on the signal output being measured, which is seldom described. It is, therefore, difficult to determine the accuracy of AT methods without characterizing gait signals first. Furthermore, much variability exists among approaches (including the numbers of body-fixed sensors and sensor locations) to obtain useful data to analyze human movement. From an end-user’s perspective, reducing the amount of sensors to one instrument that is attached to a single location on the body would greatly simplify the design and use of the system.
With this in mind, the accuracy of formerly identified or gait events from a single IMU attached to the lower trunk was explored. The study’s analysis of the trunk’s vertical and anterior-posterior acceleration pattern (and of their integrands) demonstrates, that a combination of both signals may provide more nuanced information regarding a person’s gait cycle, ultimately permitting more clinically relevant gait features to be extracted.
Going one step further, a modified step length algorithm based on a pendulum model of the swing leg was proposed. By incorporating the trunk’s anterior-posterior displacement, more accurate predictions of mean step length can be made in healthy subjects at self-selected walking speeds. Experimental results indicate that the proposed algorithm estimates step length with errors less than 3% (mean error of 0.80 ± 2.01cm). The performance of this algorithm, however, still needs to be verified for those suffering from gait disturbances.
Having established a referential framework for the extraction of temporal gait parameters as well as an algorithm for step length estimations from one instrument attached to the lower trunk, the fourth and final study explored the inertial-sensing capabilities of an iPod Touch. With the help of Dr. Ian Sheret and Oxford Brookes’ spin-off company ‘Wildknowledge’, a smart application for the iPod Touch was developed. The study results demonstrate that the proposed inertial-sensing method can reliably derive lower trunk vertical displacement (intraclass correlations ranging from .80 to .96) with similar agreement measurement levels to those gathered by a conventional inertial sensor (small systematic error of 2.2mm and a typical error of 3mm). By incorporating the aforementioned methods, an iPod Touch can potentially serve as a novel ambulatory monitor system capable of assessing gait in clinical and non-clinical environments
Hybrid wheelchair controller for handicapped and quadriplegic patients
In this dissertation, a hybrid wheelchair controller for handicapped and quadriplegic patient is proposed. The system has two sub-controllers which are the voice controller and the head tilt controller. The system aims to help quadriplegic, handicapped, elderly and paralyzed patients to control a robotic wheelchair using voice commands and head movements instead of a traditional joystick controller. The multi-input design makes the system more flexible to adapt to the available body signals. The low-cost design is taken into consideration as it allows more patients to use this system
Design of a Wearable Balance Control Indicator
Each year, one in three elderly fall. Studies show that many factors contribute to an elderly person\u27s risk of falling, but if the factors causing imbalance are improved, a person\u27s risk of falling may be reduced. A device that detects and alerts the user of an off-balance situation before the fall occurs could identify a specific need for improved balance control. This MQP describes the design, testing, and verification of a prototype wearable device that is worn on the right hip during the sit-to-stand activity (STS) to detect and notify the user of an unbalanced STS. By signaling an off-balance situation during STS, our device notifies the user of poor balance control and identifies the need for balance control improvement
Wearable and IoT technologies application for physical rehabilitation
This research consists in the development an IoT Physical Rehabilitation solution based
on wearable devices, combining a set of smart gloves and smart headband for use in
natural interactions with a set of VR therapeutic serious games developed on the Unity
3D gaming platform. The system permits to perform training sessions for hands and
fingers motor rehabilitation.
Data acquisition is performed by Arduino Nano Microcontroller computation platform
with ADC connected to the analog measurement channels materialized by piezo-resistive
force sensors and connected to an IMU module via I2C. Data communication is performed
using the Bluetooth wireless communication protocol. The smart headband, designed to
be used as a first- person-controller in game scenes, will be responsible for collecting the
patient's head rotation value, this parameter will be used as the player's avatar head
rotation value, approaching the user and the virtual environment in a semi-immersive
way.
The acquired data are stored and processed on a remote server, which will help the
physiotherapist to evaluate the patients' performance around the different physical
activities during a rehabilitation session, using a Mobile Application developed for the
configuration of games and visualization of results.
The use of serious games allows a patient with motor impairments to perform exercises
in a highly interactive and non-intrusive way, based on different scenarios of Virtual
Reality, contributing to increase the motivation during the rehabilitation process.
The system allows to perform an unlimited number of training sessions, making possible
to visualize historical values and compare the results of the different performed sessions,
for objective evolution of rehabilitation outcome. Some metrics associated with upper
limb exercises were also considered to characterize the patient’s movement during the
session.Este trabalho de pesquisa consiste no desenvolvimento de uma solução de Reabilitação
Física IoT baseada em dispositivos de vestuário, combinando um conjunto de luvas
inteligentes e uma fita-de-cabeça inteligente para utilização em interações naturais com
um conjunto de jogos terapêuticos sérios de Realidade Virtual desenvolvidos na
plataforma de jogos Unity 3D. O sistema permite realizar sessões de treino para
reabilitação motora de mãos e dedos.
A aquisição de dados é realizada pela plataforma de computação Arduino utilizando um
Microcontrolador Nano com ADC (Conversor Analógico-Digital) conectado aos canais
de medição analógicos materializados por sensores de força piezo-resistivos e a um
módulo IMU por I2C. A comunicação de dados é realizada usando o protocolo de
comunicação sem fio Bluetooth. A fita-de-cabeça inteligente, projetada para ser usada
como controlador de primeira pessoa nos cenários de jogo, será responsável por coletar o
valor de rotação da cabeça do paciente, esse parâmetro será usado como valor de rotação
da cabeça do avatar do jogador, aproximando o utilizador e o ambiente virtual de forma
semi-imersiva.
Os dados adquiridos são armazenados e processados num servidor remoto, o que ajudará
o fisioterapeuta a avaliar o desempenho dos pacientes em diferentes atividades físicas
durante uma sessão de reabilitação, utilizando uma Aplicação Móvel desenvolvido para
configuração de jogos e visualização de resultados.
A utilização de jogos sérios permite que um paciente com deficiências motoras realize
exercícios de forma altamente interativa e não intrusiva, com base em diferentes cenários
de Realidade Virtual, contribuindo para aumentar a motivação durante o processo de
reabilitação.
O sistema permite realizar um número ilimitado de sessões de treinamento, possibilitando
visualizar valores históricos e comparar os resultados das diferentes sessões realizadas,
para a evolução objetiva do resultado da reabilitação. Algumas métricas associadas aos
exercícios dos membros superiores também foram consideradas para caracterizar o
movimento do paciente durante a sessão
UTILIZING OF MEMS SENSORS IN REHABILITATION PROCESS
The potential for utilizing of MEMS sensors, especially of accelerometers and gyroscopes is significant. They are used not only in consumer’s electronics, but also in so called wearable sensors that can be worn on body or in part of garment without interrupting comfort of person who is wearing these sensors. In the same time, we are able to collect data about person carrying the device. This paper focuses on analysis of current state of utilizing of MEMS sensors in rehabilitation process or in motion analysis
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