Wireless Intelligent Pedometer for elderly patients using ARM10 (original) (raw)
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Inertial Sensor Based Stride Parameter Calculation from Gait Sequences in Geriatric Patients
IEEE transactions on bio-medical engineering, 2014
A detailed and quantitative gait analysis can provide evidence of various gait impairments in elderly people. To provide an objective decision-making basis for gait analysis, simple applicable tests analyzing a high number of strides are required. A mobile gait analysis system, which is mounted on shoes, can fulfill these requirements. This paper presents a method for computing clinically relevant temporal and spatial gait parameters. Therefore, an accelerometer and gyroscope were positioned laterally below each ankle joint. Temporal gait events were detected by searching for characteristic features in the signals. To calculate stride length, the gravity compensated accelerometer signal was double integrated and sensor drift was modeled using a piece-wise defined linear function. The presented method was validated using GAITRiteR based gait parameters from 101 patients (average age 82.1 years). Subjects performed a normal walking test with and without a wheeled walker. The parameter...
ACTIVITY RECOGNITION AND FOOTSTEP BASED GAIT ANALYSIS IN GERIATRIC PATIENTS USING INERTIAL SENSORS
The main aim of this research work is to design and implement a system for Health monitoring and fall detection in elderly people i.e,Geriatric patients accompanied by a system to perform Gait Analysis. Health monitoring involves continuous monitoring of health conditions of disabled, elderly patientsusing many measures and parameters based on Remote Patient Monitoring (RPM) technologies. Gait Analysis involves conveying important information about one’s physical and cognitive conditions using inertial sensors. Health monitoring provides a platform for monitoring health conditions like temperature, heartbeat rate of elderly citizens using an intelligent and a versatile health monitoring system that could help the elderly and individuals with disability, live independently in their own homes. If the monitored health conditions are abnormal, a message can be sent via GSM to the people concerned. It serves as a cost effective approach for personal care. Thiswork presents a foot-step analysis based gait Analysis, where certain foot-step related gait parameters are calculated from the simulated graphical values and sensors that are used for the purposes.An unobtrusive system capable of detecting accidental falls is also designed. The parameters obtained from the above mentioned systems are transmitted via GSM to the concerned health care professionals. Keywords Gait analysis, Fall detection,Health monitoring,Geriatric p
Walking Gait Measurement and Gait Parameters Extraction
2018
A fourth generation walking gait measurement device has been designed to capture and analyze detailed gait and stride metrics which eventually provides a Fall-Risk Assessment score. Specifically, the device has been modified to fit the residential environment and the elderly consumers which is low-cost, user-friendly, and portable. The gait parameters would be obtained by the on-board gait analysis protocol. Through gait parameters people’s falling risk can then be calculated so that people can be alerted to take precautionary measures before falling. Overall, the device has been made and demonstrated having better performance than its previous generations. The on-board gait analyzing program executed slower than the computer version program but has the same accuracy. However, the overall performance is better than transforming data from the measurement device to a computer manually.
Background: The assessment of short episodes of gait is clinically relevant and easily implemented, especially given limited space and time requirements. BFS (body-fixed-sensors) are small, lightweight and easy to wear sensors, which allow the assessment of gait at relative low cost and with low interference. Thus, the assessment with BFS of short episodes of gait, extracted from dailylife physical activity or measured in a standardised and supervised setting, may add value in the study of gait quality of the elderly. The aim of this study was to evaluate the accuracy of a novel algorithm based on acceleration signals recorded at different human locations (lower back and heels) for the detection of step durations over short episodes of gait in healthy elderly subjects.
A New Application of Smart Walker for Quantitative Analysis of Human Walking
Lecture Notes in Computer Science, 2015
This paper presents a new nonintrusive device for everyday gait analysis and elderly health monitoring. The system is a standard walking assistive device (rollator) equipped with light and low cost sensors: encoders and inertial measurement unit. In order to develop walking quality index, the assisted walking of 23 young adults (< 65 years) and 25 healthy elderly people (> 69 years) are compared. The subjects were asked to walk on a straight trajectory and an inverted L-shaped trajectory respectively. The user's walking trajectory, which is missing in other gait analysis methods, is calculated based on the encoder data. The Lshaped trajectory is analyzed in phases with the help of yaw angle and angular velocity signal. The calculation of trajectory and step detection are compared with the results obtained by a standard motion capture system, that is validated for biomechanical use. The results show that new index obtained by using the walker measurements, and not available otherwise, are very discriminating, e.g., the elderly have larger lateral motion and maneuver area, smaller angular velocity during turning, their walking accuracy is lower and turning ability is weaker although they have almost the same walking velocity as the young people.
Electronic device for gait analysis
Revista de Ciencia y Tecnología, 2022
In order to automate the determination of gait parameters, a system capable of acquiring data from inertial units, exploiting their maximum sampling frequency, was developed. The study of gait is one of the fundamental indicators for the evaluation of physical performance. It allows the estimation of the functional deterioration of the elderly in an objective way, so several tests have been designed to evaluate it. The system developed has two fundamental elements: an electronic device and a desktop application. The electronic device has the function of collecting data from the MPU-9255 sensor using an ESP32 to set the sampling rate, transmitting the data via WiFi to the computer and monitoring the system's battery. The desktop application allows the electronic device to be configured and controlled, as well as receiving, displaying and storing the data. As a result, a prototype capable of operating at a sampling frequency of 1 kHz was built. Tests carried out on the system demonstrate its reliability and allow the limits of sampling frequency and working distance to be set.
Wireless ambulatory monitoring system with online periodical gait assessment
International Journal of Biomedical Engineering and Technology, 2012
This paper presents wireless gait monitoring system that incorporates hardware /software co-design to measure and to record the angular rate of the lower limbs in real-time during walking as well as to periodically examine the human gait. This system integrates two new elements that enable the periodical gait assessment. The first element is a novel algorithm that integrates the multi-resolution wavelet decomposition method with peak-valley detection algorithm. This algorithm identifies the occurrences of heel-strike and toe-off, hence allows the determination of various temporal gait parameters. The second element is the Coefficient of Determination (CoD). CoD provides a single value indicator that defines the normality of a person's gait. In the experimental study, abnormal gait is artificially simulated by placing a load on one side of the limb. As a result, significant changes were found in the duration of the stance phase and swing phase and orientation of the lower extremity. Significant differences were also found in CoD between normal and abnormal gait (p<0.01). These experiments demonstrated the capability of the system in capturing a person's gait in real-time and periodically evaluating his/her gait.
Gait Disturbances in Geriatric Patients based on Activity Recognition and Footstep Monitoring
The main aim of this research work is to design and implement a system for Health monitoring and fall detection in elderly people i.e, Geriatric patients accompanied by a system to perform Gait Disturbance Analysis. Health monitoring involves continuous monitoring of health conditions of disabled, elderly patients using many measures and parameters based on Remote Patient Monitoring (RPM) technologies. Gait Analysis involves conveying important information about one's physical and cognitive conditions using inertial sensors. Health monitoring provides a platform for monitoring health conditions like temperature, heartbeat rate of elderly citizens using an intelligent and a versatile health monitoring system that could help the elderly and individuals with disability, live independently in their own homes. If the monitored health conditions are abnormal, a message can be sent via GSM to the people concerned. It serves as a cost effective approach for personal care. An unobtrusive system capable of detecting accidental falls is also designed. The parameters obtained from the above mentioned systems are transmitted via GSM to the concerned health care professionals for smooth monitoring of gait disturbances in the elderly patients.
Benini L: A Wireless System for Gait and Posture Analysis Based
2015
Abstract- In this paper we describe a wireless wearable system to monitor gait, based on a customized pair of commercial insoles able to collect ground reaction forces by use of 24 embedded cells for each foot. Each insole was combined with a small form factor, low-power Inertial Measurement Unit (IMU) and enabled to communicate via Bluetooth with a base station. We present here the characterization of the system both in terms of performance and in terms of functionality. The system was tested on a subject to demonstrate the usability and the features extraction during gait; this data allow to recognize walking phase in terms of swing and stance phase, step and stride duration, double support and single support duration, both using the pressure sensors and the IMU.