A System for Monitoring Stroke Patients in a Home Environment (original) (raw)
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Daily-life monitoring of stroke survivors motor performance: The INTERACTION sensing system
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
The objective of the INTERACTION Eu project is to develop and validate an unobtrusive and modular system for monitoring daily life activities, physical interactions with the environment and for training upper and lower extremity motor function in stroke subjects. This paper describes the development and preliminary testing of the project sensing platform made of sensing shirt, trousers, gloves and shoes. Modular prototypes were designed and built considering the minimal set of inertial, force and textile sensors that may enable an efficient monitoring of stroke patients. The single sensing elements are described and the results of their preliminary lab-level testing are reported.
Daily-life tele-monitoring of motor performance in stroke survivors
the objective of the EU project INTERACTION is to develop an unobtrusive and modular sensing system for objective monitoring of daily-life motor performance of stroke survivors. This will enable clinical professionals to advise their patients about their continued daily-life activity profile and home training, and evaluate and optimize rehabilitation programs. A modular textile-integrated sensing system was developed and performance and capacity measures were proposed and clinically tested in stroke subjects. Telemonitoring facilities were developed and tested. In the last stage of the project, the system will be tested during daily-life.
A Framework for (Tele-) Monitoring of the Rehabilitation Progress in Stroke Patients
Applied Clinical Informatics, 2015
SummaryBackground: Preservation of mobility in conjunction with an independent life style is one of the major goals of rehabilitation after stroke.Objectives: The Rehab@Home framework shall support the continuation of rehabilitation at home.Methods: The framework consists of instrumented insoles, connected wirelessly to a 3G ready tablet PC, a server, and a web-interface for medical experts. The rehabilitation progress is estimated via automated analysis of movement data from standardized assessment tests which are designed according to the needs of stroke patients and executed via the tablet PC application.Results: The Rehab@Home framework’s implementation is finished and ready for the field trial (at five patients’ homes). Initial testing of the automated evaluation of the standardized mobility tests shows reproducible results.Conclusions: Therefore it is assumed that the Rehab@Home framework is applicable as monitoring tool for the gait rehabilitation progress in stroke patients.
Renovo: Prototype of a Low-Cost Sensor-Based Therapeutic System for Upper Limb Rehabilitation
Cornell University - arXiv, 2021
Stroke patients with Upper Limb Disability (ULD) are re-acclimated to their lost motor capability through therapeutic interventions, following assessment by Physiotherapists (PTs) using various qualitative assessment protocols. However, the assessments are often biased and prone to errors. Real-time visualization and quantitative analysis of various Performance Metrics (PMs) of patient's motion data, such as-Range of Motion (RoM), Repetition Rate (RR), Velocity (V), etc., may be vital for proper assessment. In this study, we present Renovo, a wearable inertial sensor-based therapeutic system, which assists PTs with real-time visualization and quantitative patient assessment, while providing patients with progress feedback. We showcase the results of a three-week pilot study on the rehabilitation of ULD patients (N=16), in 3 successive sessions at one-week interval, following evaluation both by Renovo and PTs (N=5). Results suggest that sensor-based quantitative assessment reduces the possibility of human error and bias, enhancing efficiency of rehabilitation. CCS Concepts: • Human-centered computing → Visualization systems and tools; Field studies; Gestural input; Graphical user interfaces; • Computer systems organization → Sensor networks; • Applied computing → Life and medical sciences.
Use of inertial sensors to measure upper limb motion: application in stroke rehabilitation
2010
Stroke is the largest cause of severe adult complex disability, caused when the blood supply to the brain is interrupted, either by a clot or a burst blood vessel. It is characterised by deficiencies in movement and balance, changes in sensation, impaired motor control and muscle tone, and bone deformity. Clinically applied stroke management relies heavily on the observational opinion of healthcare workers. Despite the proven validity of a few clinical outcome measures, they remain subjective and inconsistent, and suffer from a lack of standardisation. Motion capture of the upper limb has also been used in specialised laboratories to obtain accurate and objective information, and monitor progress in rehabilitation. However, it is unsuitable in environments that are accessible to stroke patients (for example at patients’ homes or stroke clubs), due to the high cost, special set-up and calibration requirements. The aim of this research project was to validate and assess the sensitivit...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019
Maximizing the motor practice in stroke survivors' living environments may significantly improve the functional recovery of their stroke-affected upper-limb. A wearable system that can continuously monitor upper-limb performance has been considered as an effective clinical solution for its potential to provide patient-centered, data-driven feedback to improve the motor dosage. Towards that end, we investigate a system leveraging a pair of finger-worn, ring-type accelerometers capable of monitoring both gross-arm and fine-hand movements that are clinically relevant to the performance of daily activities. In this work, we conduct a mixed-methods study to (1) quantitatively evaluate the efficacy of finger-worn accelerometers in measuring clinically relevant information regarding stroke survivors' upper-limb performance, and (2) qualitatively investigate design requirements for the self-monitoring system, based on data collected from 25 stroke survivors and seven occupational th...
Topics in Stroke Rehabilitation, 2014
Background: An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation fi eld to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for effi cient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, effi cient, and cost-effective delivery system. This study aims to assist physiotherapists' clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system. Methods: A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 fi rst-time poststroke patients during a reach-press-return task. Results: Preliminary studies revealed acceleration profi les of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help defi ne proper movement. Conclusion: An inertial data acquisition system was designed and developed as a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profi les and aid the development of quantifi able methodologies and protocols.
Development of a wearable ZigBee sensor system for upper limb rehabilitation robotics
2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 2012
This paper presents a new tool for assessment and therapy in post-stroke upper-limb rehabilitation and a new wireless sensor technology to enhance rehabilitation robotics based on the ZigBee network of wearable Inertial Measurement Units (IMU) and Surface Electromyography (sEMG) sensor nodes. These sensor nodes will allow the measurement of kinematic and electrical muscle activity of patients in continuous therapy motion over all body segments as a Body Sensor Network (BSN). The IMU Sensor design was based on a direction-cosine-matrix DCM. The system validation was achieved with an optical motion tracking system in which cameras and IMU sensors recorded upper limb positions simultaneously during a standard gesture of reaching and grasping. The comparison between elbow flexion-extension angle in reaching and grasping movements obtained from both techniques shows equivalence. The analysis of IMU data signals for several movements demonstrates high repeatability intra and inter-subjects. I. INTRODUCTION stroke is the consequence of cell death within the brain relating to either internal bleeding or a blockage in one of the two main supplying arteries. Currently, it represents a major problem in clinical medicine being a leading cause of disability in the developed world [1]. Worldwide, 15 million people suffer a stroke, of which, 5 million die and another 5 million are left permanently disabled. Strokes are uncommon in people under 40 years; when they do occur, the main risk factor is high blood pressure [2]. Strokes remain a major public health concern in the United States, with more than 795,000 cases diagnosed annually. Over 50% of subjects present some paresis [3].
A design framework for a home-based stroke rehabilitation system: identifying the key components
Pervasive …, 2009
We present a design framework for a sensor-based stroke rehabilitation system for use at home developed through the analysis of data collected from a series of workshops. Participants had a variety of backgrounds and included people living with stroke and health professionals who work with them. Our focus in these workshops was to learn more about the social context around stroke care, to share early project ideas and develop a design framework for developing systems. In this paper we present a detailed analysis of participant responses and use this analysis to draw specific conclusions about the components and configuration that we believe should be in future systems.
Frontiers in Bioengineering and Biotechnology
The development of context-appropriate sensor technologies could alleviate the significant burden of stroke in Sub-Saharan African rehabilitation clinicians and health care facilities. However, many commercially available wearable sensors are beyond the financial capabilities of the majority of African persons. In this study, we evaluated the concurrent validity of a low-cost wearable sensor (i.e., the outREACH sensor) to measure upper limb movement kinematics of 31 healthy persons, using an 8-camera Vicon motion capture system as the reference standard. The outREACH sensor showed high correlation (r range: 0.808-0.990) and agreement (mean difference range: −1.60 to 1.10) with the reference system regardless of task or kinematic parameter. Moreover, Bland-Altman analyses indicated that there were no significant systematic errors present. This study indicates that upper limb movement kinematics can be accurately measured using the outREACH sensor, and have the potential to enhance stroke evaluation and rehabilitation in sub-Saharan Africa.