An instrumental approach for monitoring physical exercises in a visual markerless scenario: A proof of concept (original) (raw)
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— This work deals with the design of an interactive monitoring tool for home-based physical rehabilitation. The software platform includes a video processing stage and the exercise performance evaluation. Image features are extracted by a Kinect v2 sensor and elaborated to return the exercises score. Furthermore the tool provides to physiotherapists a quantitative exercise evaluation of subject's performances. The proposed tool for home rehabilitation has been tested on 5 subjects and 5 different exercises and results are presented. In particular both exercises and relative evaluation indexes were selected by specialists in neurorehabilitation.
A Kinect-based rehabilitation exercise monitoring and guidance system
2014 IEEE 5th International Conference on Software Engineering and Service Science, 2014
In this paper, we describe the design and implementation of a Kinect-based system for rehabilitation exercises monitoring and guidance. We choose to use the Unity framework to implement our system because it enables us to use virtual reality techniques to demonstrate detailed movements to the patient, and to facilitate examination of the quality and quantity of the patient sessions by the clinician. The avatar-based rendering of motion also preserves the privacy of the patients, which is essential for healthcare systems. The key contribution of our research is a rule-based approach to realtime exercise quality assessment and feedback. We developed a set of basic rule elements that can be used to express the correctness rules for common rehabilitation exercises.
Archives of Physiotherapy and Global Researches, 2016
From a cibernetic approach, the body system can be defined like a net of structural and functional related subsystems with motor equifinality inside the concept of balance, energetic economy and comfort: therefore the ideal posture is the one that allows the maximum effectiveness of motor gesture, in absence of pain with the maximum energetic economy. The present study research is based on the necessity to individuate a real objective evaluation system of the postural parameters, inexpensive and of simple use compared to the evaluation instruments in use already scientifically validated. The instrument used in this study is the Microsoft Kinect®, gaming platform combined with the Xbox console. Created by Microsoft in the field of play, the Microsoft Kinect® for years has entertained millions of consumers through the Motion Capture System, the recording of movement through cameras and instant or deferred replay. The primary aim of this randomized controlled single-blind research is the demonstration that, despite being commonly defined objective the evaluation systems that utilize markers, is essential to look for an alternative evaluation method to minimize the systematic human error. The results demonstrate the real validity of Kinect®, and have verified the reliability of the data obtained from the assessment, showing the scientific reliability of this innovative objective evaluation method in rehabilitation-clinical field.
Kinect-Based Physiotherapy and Assessment: A Comprehensive Review
Indonesian Journal of Electrical Engineering and Computer Science, 2018
Kinect-based physical rehabilitation grows significantly as a mechanism for clinical assessment and rehabilitation due to its flexibility, low-cost and markerless system for human action capture. It is also an approach to provide convenience for for patients’ exercises continuation at home. In this paper, we discuss a review of the present Kinect-based physiotherapy and assessment for rehabilitation patients to provide an outline of the state of art, limitation and issues of concern as well as suggestion for future work in this approach. The paper is constructed into three main parts. The introduction was discussed on physiotherapy exercises and the limitation of current Kinect-based applications. Next, we also discuss on Kinect Skeleton Joint and Kinect Depth Map features that being used widely nowadays. A concise summary with significant findings of each paper had been tabulate for each feature; Skeleton Joints and Depth Map. Afterwards, we assemble a quite number of classificati...
Statistical Validation for Clinical Measures: Repeatability and Agreement of Kinect™-Based Software
BioMed research international, 2018
The rehabilitation process is a fundamental stage for recovery of people's capabilities. However, the evaluation of the process is performed by physiatrists and medical doctors, mostly based on their observations, that is, a subjective appreciation of the patient's evolution. This paper proposes a tracking platform of the movement made by an individual's upper limb using Kinect sensor(s) to be applied for the patient during the rehabilitation process. The main contribution is the development of quantifying software and the statistical validation of its performance, repeatability, and clinical use in the rehabilitation process. The software determines joint angles and upper limb trajectories for the construction of a specific rehabilitation protocol and quantifies the treatment evolution. In turn, the information is presented via a graphical interface that allows the recording, storage, and report of the patient's data. For clinical purposes, the software information ...
RehabGesture: An Alternative Tool for Measuring Human Movement
Telemedicine and e-Health, 2016
Background: Systems for range of motion (ROM) measurement such as OptoTrak, Motion Capture, Motion Analysis, Vicon, and Visual 3D are so expensive that they become impracticable in public health systems and even in private rehabilitation clinics. Telerehabilitation is a branch within telemedicine intended to offer ways to increase motor and/or cognitive stimuli, aimed at faster and more effective recovery of given disabilities, and to measure kinematic data such as the improvement in ROM. Materials and Methods: In the development of the RehabGesture tool, we used the gesture recognition sensor Kinect Ò (Microsoft, Redmond, WA) and the concepts of Natural User Interface and Open Natural Interaction. Results: RehabGesture can measure and record the ROM during rehabilitation sessions while the user interacts with the virtual reality environment. The software allows the measurement of the ROM (in the coronal plane) from 0°extension to 145°flexion of the elbow joint, as well as from 0°a dduction to 180°abduction of the glenohumeral (shoulder) joint, leaving the standing position. The proposed tool has application in the fields of training and physical evaluation of professional and amateur athletes in clubs and gyms and may have application in rehabilitation and physiotherapy clinics for patients with compromised motor abilities. Conclusions: RehabGesture represents a low-cost solution to measure the movement of the upper limbs, as well as to stimulate the process of teaching and learning in disciplines related to the study of human movement, such as kinesiology.
2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), 2014
In this paper, we present a feasibility study for using a single Microsoft Kinect sensor to assess the quality of rehabilitation exercises. Unlike competing studies that have focused on the validation of the accuracy of Kinect motion sensing data at the level of joint positions, joint angles, and displacement of joints, we take a rule based approach. The advantage of our approach is that it provides a concrete context for judging the feasibility of using a single Kinect sensor for rehabilitation exercise monitoring. Our study aims to answer the following question: if it is found that Kinect's measurement on a metric deviates from the ground truth by some amount, is this an acceptable error? By defining a set of correctness rules for each exercise, the question will be answered definitively with no ambiguity. Defining appropriate context in a validation study is especially important because (1) the deviation of Kinect measurement from the ground truth varies significantly for different exercises, even for the same joint, and (2) different exercises have different tolerance levels for the movement restrictions of body segments. In this study, we also show that large but systematic deviations of the Kinect measurement from the ground truth are not as harmful as it seems because the problem can be overcome by adjusting parameters in the correctness rules.
Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect
2020
Accessibility and inclusiveness of people with disabilities is a recurring theme that is already perceived as an issue in the field of human rights. Ramps, elevators, among other devices aim at the inclusion of these individuals with limited mobility. Various types of motor limitations, specially partial limitations, are linked to corresponding physical-motor rehabilitation process, with the purpose of reducing or eliminating the patient's dependence on a caregiver or devices for adaptation. Patients with motor disabilities must practice physiotherapeutical exercises along a physician in order to perform body and muscle analysis to ensure the patient's well-being. To reach a more accurate analysis, physiotherapists use a range of devices to acquire patient data, such as the spirometer, to acquire the patient's breath intensity and lung capacity. Similarly, there are other technologies capable of acquiring motion data and quantifying them. This work aims to develop a system that, paired together with an exercise game project (exergame), can acquire and transmit the motion data acquired in-game for an easier and faster analysis of the patient's growth, relying on graphs, tables, and other visual indicators to improve the evaluation of physiotherapeutic treatments. The usage together with an exergame also has benefits such as increased patient compliance with the treatment and improvements in well-being.
Multimedia Tools and Applications, 2019
Exercise therapy is a conventional intervention for stroke rehabilitation. Performance monitoring and feedback have shown to further improve the outcome of exercise therapy. This paper proposes a vision based system for monitoring exercise therapy which consists of 3 components: online exercise recognition, exercise performance analysis, and automatic visual feedback generation. The Microsoft Kinect was used for data acquisition. The exercise recognition component utilizes Kinect joints to continuously recognize and track the exercises. Upon completion of each exercise, joint flexibility and compensatory trunk motions are extracted for performance analysis. The visual feedback is a virtual skeleton augmented on top of the Kinect skeleton which displays the correct exercise path during execution. The Kinect skeleton and exercise definitions were applied to a motion hierarchy and animated using forward kinematics. Two additional experiments were also conducted to find accurate methods for calculating joint flexibility based on ROM measurement and trunk representation. Several datasets were created for system design and evaluation: 336 exercise sequences for exercise recognition, 25 records for ROM measurement, and 63 records for finding a suitable trunk representation method and compensatory motion detection. System evaluations showed that each component of the system is capable of producing outputs with significant accuracy.