scholarly journals 2Vita-B Physical: An Intelligent Home Rehabilitation System Based on Microsoft Azure Kinect

2021 ◽  
Vol 3 ◽  
Author(s):  
Mauro Antico ◽  
Nicoletta Balletti ◽  
Andrea Ciccotelli ◽  
Marco Ciccotelli ◽  
Gennaro Laudato ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Microsoft Kinect ◽  
Drastic Reduction ◽  
Motor Disabilities ◽  
Non Invasive ◽  
Intelligent Home ◽  
Rehabilitation System ◽  
Correct Execution ◽  
Active Rehabilitation ◽  
Motion Capturing

Active rehabilitation is an exercise-based program designed to improve the level of function of people with motor disabilities. The effectiveness of such programs is strongly influenced by the correctness of the exercise execution. An exercise done incorrectly could even lead to a worsening of the health status. For this reason, specialists are required to guide the patient during the execution of an exercise. The drastic reduction of the costs of motion tracking systems has paved the way to the implementation of virtual assistant software able to automatically assess the correctness of an exercise. In this paper 2Vita-B Physical is presented, a rehabilitation software system properly designed to support both 1) the patients, by guiding them in the correct execution of an exercise; and 2) the physiotherapists, by allowing them to remotely check the progress of a patient. The motion capturing in 2Vita-B is performed by using the recently released Microsoft Kinect Azure DK. Thus, the system is easy to use and completely non-invasive. Besides the hardware and software requirements of the system, the results of a preliminary usability evaluation of the system conducted with 29 users is also reported. The results achieved are promising and provide evidence of the high usability of 2Vita-B Physical as home rehabilitation system.

scholarly journals Kinect Fusion improvement using depth camera calibration

2014 ◽  
Vol XL-5 ◽  
pp. 479-485 ◽  
Author(s):  
D. Pagliari ◽  
F. Menna ◽  
R. Roncella ◽  
F. Remondino ◽  
L. Pinto
Keyword(s):  
Video Game ◽  
Motion Tracking ◽  
Microsoft Kinect ◽  
Third Party ◽  
Depth Sensor ◽  
Ir Camera ◽  
3D Data ◽  
Reconstruction Software ◽  
Remote Controller ◽  
Accuracy And Repeatability

Scene's 3D modelling, gesture recognition and motion tracking are fields in rapid and continuous development which have caused growing demand on interactivity in video-game and e-entertainment market. Starting from the idea of creating a sensor that allows users to play without having to hold any remote controller, the Microsoft Kinect device was created. The Kinect has always attract researchers in different fields, from robotics to Computer Vision (CV) and biomedical engineering as well as third-party communities that have released several Software Development Kit (SDK) versions for Kinect in order to use it not only as a game device but as measurement system. Microsoft Kinect Fusion control libraries (firstly released in March 2013) allow using the device as a 3D scanning and produce meshed polygonal of a static scene just moving the Kinect around. A drawback of this sensor is the geometric quality of the delivered data and the low repeatability. For this reason the authors carried out some investigation in order to evaluate the accuracy and repeatability of the depth measured delivered by the Kinect. The paper will present a throughout calibration analysis of the Kinect imaging sensor, with the aim of establishing the accuracy and precision of the delivered information: a straightforward calibration of the depth sensor in presented and then the 3D data are correct accordingly. Integrating the depth correction algorithm and correcting the IR camera interior and exterior orientation parameters, the Fusion Libraries are corrected and a new reconstruction software is created to produce more accurate models.

Design and Development of Intelligent Home Rehab Device for Post Stroke Therapy with Electro-Hydraulic Interventions

2021 ◽  
Author(s):  
Kalaiarasi Arumugam ◽  
L.Ashok Kumar
Keyword(s):  
Daily Living ◽  
Low Cost ◽  
Complete Recovery ◽  
Hydraulic Systems ◽  
Upper Arm ◽  
Survival Group ◽  
Intelligent Home ◽  
Home Based ◽  
Rehabilitation System ◽  
Life Threatening

Today, brain attack disorders are one of the most life-threatening areas in the medical era, which mankind is facing nowadays. Globally, more than 10,000,000 people are subjected to brain attack disorders like hemiplegia and tremor, every year, where two-thirds of them survive. Among the survival community, more than 80 per cent of them are subjected to long-term impairment of their upper extremity. In order to treat the impairment, the survival group is subjected to medications and rehabilitation in order to improve their daily living. But the facilities are very limited in fast-developing countries like India when compared to western standards. The rehabilitation given corresponding with medications during the treatment period in hospitals does not give a complete recovery from disability. People from rural background could not meet their rehabilitation requirements even in the hospital during treatment and also when they are discharged to home after treatment from hospitals due to financial constraints and reachability. In order to motivate the survival group to fulfill their daily living and improve their lifestyle, this paper is focused on intelligent home-based rehabilitation system at low cost, reliability, and affordability. One major movement disorder namely Upper Arm Hemiplegia was taken into account and visited few major hospitals around Coimbatore and Chennai for literature and case study. The facilities available in various hospitals and their drawbacks were analyzed.Acupuncture & Electro-therapeutics Research E-pubBased on the studies conducted at hospitals and taking advice from therapists, an innovative low-cost home-based rehabilitation device using Electro-Hydraulic systems has been developed to support patients who were used to impaired living even after treatments. To support Upper Arm Hemiplegia patients, the devices which were developed and experimented to hold different functionalities are discussed in this paper.

scholarly journals Marker-based motion tracking using Microsoft Kinect

2018 ◽  
Vol 51 (22) ◽  
pp. 399-404 ◽  
Author(s):  
Alireza Bilesan ◽  
Mohammadhasan Owlia ◽  
Saeed Behzadipour ◽  
Shuhei Ogawa ◽  
Teppei Tsujita ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Microsoft Kinect

scholarly journals Design and Analysis of Cloud Upper Limb Rehabilitation System Based on Motion Tracking for Post-Stroke Patients

2019 ◽  
Vol 9 (8) ◽  
pp. 1620 ◽  
Author(s):  
Bai ◽  
Song ◽  
Li
Keyword(s):  
Upper Limb ◽  
Motion Tracking ◽  
Stroke Patients ◽  
Mean Velocity ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Post Stroke ◽  
Reachable Workspace ◽  
Rehabilitation System ◽  
Limb Rehabilitation

In order to improve the convenience and practicability of home rehabilitation training for post-stroke patients, this paper presents a cloud-based upper limb rehabilitation system based on motion tracking. A 3-dimensional reachable workspace virtual game (3D-RWVG) was developed to achieve meaningful home rehabilitation training. Five movements were selected as the criteria for rehabilitation assessment. Analysis was undertaken of the upper limb performance parameters: relative surface area (RSA), mean velocity (MV), logarithm of dimensionless jerk (LJ) and logarithm of curvature (LC). A two-headed convolutional neural network (TCNN) model was established for the assessment. The experiment was carried out in the hospital. The results show that the RSA, MV, LC and LJ could reflect the upper limb motor function intuitively from the graphs. The accuracy of the TCNN models is 92.6%, 80%, 89.5%, 85.1% and 87.5%, respectively. A therapist could check patient training and assessment information through the cloud database and make a diagnosis. The system can realize home rehabilitation training and assessment without the supervision of a therapist, and has the potential to become an effective home rehabilitation system.

Feasibility study of using a Microsoft Kinect for virtual coaching of wheelchair transfer techniques

2017 ◽  
Vol 62 (3) ◽  
Author(s):  
Seonhong Hwang ◽  
Chung-Ying Tsai ◽  
Alicia M. Koontz
Keyword(s):  
Motion Tracking ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Transfer Task ◽  
Angle Measurement ◽  
Microsoft Kinect ◽  
Joint Angles ◽  
Wheelchair Users ◽  
Small Standard Error ◽  
Mean Square Errors

AbstractThe purpose of this study was to test the concurrent validity and test-retest reliability of the Kinect skeleton tracking algorithm for measurement of trunk, shoulder, and elbow joint angle measurement during a wheelchair transfer task. Eight wheelchair users were recruited for this study. Joint positions were recorded simultaneously by the Kinect and Vicon motion capture systems while subjects transferred from their wheelchairs to a level bench. Shoulder, elbow, and trunk angles recorded with the Kinect system followed a similar trajectory as the angles recorded with the Vicon system with correlation coefficients that are larger than 0.71 on both sides (leading arm and trailing arm). The root mean square errors (RMSEs) ranged from 5.18 to 22.46 for the shoulder, elbow, and trunk angles. The 95% limits of agreement (LOA) for the discrepancy between the two systems exceeded the clinical significant level of 5°. For the trunk, shoulder, and elbow angles, the Kinect had very good relative reliability for the measurement of sagittal, frontal and horizontal trunk angles, as indicated by the high intraclass correlation coefficient (ICC) values (>0.90). Small standard error of the measure (SEM) values, indicating good absolute reliability, were observed for all joints except for the leading arm’s shoulder joint. Relatively large minimal detectable changes (MDCs) were observed in all joint angles. The Kinect motion tracking has promising performance levels for some upper limb joints. However, more accurate measurement of the joint angles may be required. Therefore, understanding the limitations in precision and accuracy of Kinect is imperative before utilization of Kinect.

scholarly journals Evaluation of real time motion tracking accuracy of customised IMU sensor for application in a mobile badminton virtual reality training system

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Zahari Taha ◽  
Mohd Yashim Wong ◽  
Hwa Jen Yap ◽  
Amirul Abdullah ◽  
Wee Kian Yeo
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Motion Tracking ◽  
Training System ◽  
Microsoft Kinect ◽  
Measurement Unit ◽  
Tracking Accuracy ◽  
Improve Performance ◽  
Motion Data ◽  
Time Motion

Immersion is one of the most important aspects in ensuring the applicability of Virtual Reality systems to training regimes aiming to improve performance. To ensure that this key aspect is met, the registration of motion between the real world and virtual environment must be made as accurate and as low latency as possible. Thus, an in-house developed Inertial Measurement Unit (IMU) system is developed for use in tracking the movement of the player’s racquet. This IMU tracks 6 DOF motion data and transmits it to the mobile training system for processing. Physically, the custom motion is built into the shape of a racquet grip to give a more natural sensation when swinging the racquet. In addition to that, an adaptive filter framework is also established to cope with different racquet movements automatically, enabling real-time 6 DOF tracking by balancing the jitter and latency. Experiments are performed to compare the efficacy of our approach with other conventional tracking methods such as the using Microsoft Kinect. The results obtained demonstrated noticeable accuracy and lower latency when compared with the aforementioned methods.

scholarly journals A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Hossein Mousavi Hondori ◽  
Maryam Khademi
Keyword(s):  
Cerebral Palsy ◽  
Physical Therapy ◽  
Neurological Disorders ◽  
The Elderly ◽  
Medical Application ◽  
Clinical Impact ◽  
Microsoft Kinect ◽  
Clinical Validation ◽  
Search Results ◽  
Rehabilitation System

This paper reviews technical and clinical impact of the Microsoft Kinect in physical therapy and rehabilitation. It covers the studies on patients with neurological disorders including stroke, Parkinson’s, cerebral palsy, and MS as well as the elderly patients. Search results in Pubmed and Google scholar reveal increasing interest in using Kinect in medical application. Relevant papers are reviewed and divided into three groups: (1) papers which evaluated Kinect’s accuracy and reliability, (2) papers which used Kinect for a rehabilitation system and provided clinical evaluation involving patients, and (3) papers which proposed a Kinect-based system for rehabilitation but fell short of providing clinical validation. At last, to serve as technical comparison to help future rehabilitation design other sensors similar to Kinect are reviewed.

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