Posts Tagged Kinect

[BOOK Chapter] The “Arm” Line of Devices for Neurological Rehabilitation: Engineering Book Chapter – Abstract

Abstract

In the modern scenario of neurological rehabilitation, which requires affordable solutions oriented toward promoting home training, the Institute of Industrial Technologies and Automation (ITIA) of the Italian National Research Council (CNR) developed a line of prototypal devices for the rehabilitation of the upper limb, called “Arm.” Arm devices were conceived to promote rehabilitation at affordable prices by capturing all the main features of the state-of-the-art devices. In fact, Arm devices focus on the main features requested by a robot therapist: mechanical adaptation to the patient, ranging from passive motion to high transparency, assist-as-needed and resistive modalities; proper use of sensors for performance monitoring; easy-to-use, modular, and adaptable design. These desirable features are combined with low-cost, additive manufacturing procedures, with the purpose of meeting the requirements coming from research on neuro-motor rehabilitation and motor control and coupling them with the recent breakthrough innovations in design and manufacturing.

The “Arm” Line of Devices for Neurological Rehabilitation

Copyright: © 2018 |Pages: 30

DOI: 10.4018/978-1-5225-2993-4.ch007

 

 

Introduction

 The use of robotic devices for upper-limb neuro-motor rehabilitation is usual practice in clinical centers. In respect to conventional therapies, robots allow to increase training intensity and help patients to promote their active contribution. Furthermore, robots can act as measurers of patients’ performances and adapt their interaction modalities to the emerging needs during the rehabilitation course. Robots like ARMin, MIT Manus, Armeo Spring, Braccio di Ferro, represent the state of the art devices for rehabilitation of the upper-limb and for promoting motor recovery. According to the available assessments and studies in the literature, their efficacy is slightly/moderately higher than the one of conventional therapies. Furthermore, robots are used in research to learn more about physiological and pathological motor control and neuromuscular diseases. Unfortunately, while being the state of the art devices for neuro-motor stimulation and training, such robots are very expensive and not compliant to user-friendly requirements that are needed for semi-autonomous home use. Consequently, they can be used only in clinical environments, under the supervision of medical personnel. Furthermore, sanitary costs related to rehabilitation are increasing and clinical centers can hardly support their burden. The possibility of delocalizing rehabilitation from clinical centers opens the chance for training performed in home environment, with time and costs savings for both the sanitary system and patients. In this scenario, which requires affordable solutions oriented toward promoting home training, the Institute of Industrial Technologies and Automation (ITIA) of the Italian National Research Council (CNR) developed a line of prototypal devices for the rehabilitation of the upper-limb, called -ArmArm devices were conceived to test the possibility of promoting rehabilitation at affordable prices but capturing all the main features of the state of the art devices. In fact, Arm devices focus on the main features requested by a robot therapist: mechanical adaptation to the patient, ranging from passive motion to high transparency, assist-as-needed and resistive modalities; proper use of sensors for performance monitoring; easy-to-use, modular and adaptable design. These desirable features are combined with low-cost, additive manufacturing procedures, with the purpose of meeting the requirements coming from research on neuro-motor rehabilitation and motor control and coupling them with the recent breakthrough innovations in design and manufacturing. Arm devices cover both clinical and home-oriented training and are designed for adaptation to patients with different motor impairment.

The Arm prototypes are:

  • • LINarm: linear device, freely orientable in space, suitable for functional movements. It features a variable stiffness actuation, allowing to adapt the mechanical behavior of the device to patients’ needs. Functional Electrical Stimulation, simple Virtual Environments and a Patient Model, gathering data from integrated sensors and modulating the level of assistance, are integrated in the set-up. The LINarm++ Echord++ Project ended in October 2016 and guided the development of a second, more refined prototype, enhancing the original concept.
  • • PLANarm: planar device, freely orientable in space, suitable for planar functional movements. The state of the art planar robots used in literature for motor control and motor learning research inspired PLANarm. It features a variable stiffness actuation, allowing adapting the mechanical behavior of the device depending on patients’ needs.
  • • DUALarm: Low-Cost device for bimanual rehabilitation, exploiting the capability of the less affected limb to provide rehabilitation to the more affected limb. DUALarm is completely realized in 3D printing technology and aims at being an easy-to-use, low-cost, open-source project. Currently, reaching movements can be trained, but the device is conceived to be suitable for training of other functional gestures.
  • • LIGHTarm: Exoskeleton for the rehabilitation of the upper-limb, designed in two versions: LIGHTarm, not actuated, and conceived to support the weight of the impaired limb. The mechanical design includes high backdrivability, focusing on shoulder rhythm and elbow singular configurations.
  • • VIRTUALarm: Kinect One-based platform for motor monitoring, including body and limb tracking and a biomechanical evaluation of the performance in relation to databases of healthy subjects. Assessments include range of motion, motion dynamics, effort, motor control indexes, body segments barycenter tracking.

via The “Arm” Line of Devices for Neurological Rehabilitation: Engineering Book Chapter | IGI Global

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[ARTICLE] Kinect-based individualized upper extremity rehabilitation is effective and feasible for individuals with stroke using a transition from clinic to home protocol – Full Text PDF

Purpose: To investigate the effectiveness and feasibility of Kinect-based upper
extremity rehabilitation on functional performance in chronic stroke survivors.
Methods: This was a single cohort pre-post test study. Participants (N=10; mean age =
62.5 ± 9.06) engaged in Kinect-based training three times a week for four to five weeks
in a university laboratory. To simulate a clinic to home transfer condition,
individualized guidance was given to participants at the initial three sessions followed
by independent usage. Outcomes included Fugl-Meyer assessment of upper extremity,
Wolf Motor Function Test, Stroke Impact Scale, Confidence of Arm and Hand
Movement and Active Range of Motion. Participant experience was assessed using a
structured questionnaire and a semi-structured interview.
Results. Improvement was found in Fugl-Meyer assessment scores (p=0.001), Wolf
Motor Function Test, (p=0.008), Active Range of Motion (p<0.05) and Stroke Impact
Scale-Hand function (p=0.016). Clinically important differences were found in FuglMeyer
assessment scores (Δ= 5.70 ± 3.47) and Wolf Motor Function Test (Δ Time= –
4.45 ± 6.02; ∆ Functional Ability Scores= 0.29 ± 0.31). All participants could use the
system independently and recognized the importance of exercise individualization by
the therapist.
Conclusions. The Kinect-based UE rehabilitation provided clinically important
functional improvements to our study participants.

Introduction

Stroke is the leading cause of long-term adult disability in the United States [1].
More than a half of survivors continue suffering from upper-limb hemiparesis poststroke with only 5% of people recovering their full arm function [2]. The persistent
upper-limb dysfunction significantly impairs motor performance, and results in a
serious decline in functional ability as well as quality of life [3]. Intensive and repeated
practice with the paretic arm appears necessary to enhance arm recovery and facilitate
neural reorganization [4-7]. Nevertheless, the healthcare system provides limited
amounts and duration of therapy, making it difficult for stroke survivors to achieve
maximal arm recovery before discharge from outpatient rehabilitation or home care
[8,9]. Therefore, identifying novel modalities that are accessible and affordable to the
general public while allowing continued practice of the arm is imperative for improving
long-term upper-limb outcomes after stroke.
One potential approach is the use of low-cost virtual reality (VR)-based systems,
for example, the Microsoft Kinect system. The Kinect is a vision-based motion
capturing system that can detect gesture and movements of the body through its RGA
camera and depth sensors. It allows users to interact with the VR-based system without
holding or wearing specialized equipment or markers for tracking. Users can play
games or practice exercises using natural movements while observing the performance of their virtual avatars shown in real-time on the computer screen. Through this interactive observation and feedback, stroke survivors can correct their movements towards more normal patterns. Furthermore, the Kinect is small and portable, thus enabling stroke survivors to practice exercises in a familiar and private environment. […]

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[Abstract+References] A Computer-Assisted System with Kinect Sensors and Wristband Heart Rate Monitors for Group Classes of Exercise-Based Rehabilitation

Abstract

Exercise-based rehabilitation for chronic conditions such as cardiovascular disease, diabetes, and chronic obstructive pulmonary disease, constitutes a key element in reducing patient symptoms and improving health status and quality of life. However, group exercise in rehabilitation programmes faces several challenges imposed by the diversified needs of their participants. In this direction, we propose a novel computer-assisted system enhanced with sensors such as Kinect cameras and wristband heart rate monitors, aiming to support the trainer in adapting the exercise programme on-the-fly, according to identified requirements. The proposed system design facilitates maximal tailoring of the exercise programme towards the most beneficial and enjoyable execution of exercises for patient groups. This work contributes in the design of the next-generation of computerised systems in exercise-based rehabilitation.

References

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    Thompson PD, Arena R, Riebe D, Pescatello LS (2013) ACSM’s new preparticipation health screening recommendations from ACSM’s guidelines for exercise testing and prescription, 9th (edn). Curr Sports Med Rep 12:215–217.  https://doi.org/10.1249/JSR.0b013e31829a68cf
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    Raedeke TD (2007) The relationship between enjoyment and affective responses to exercise. J Appl Sport Psychol 19:105–115.  https://doi.org/10.1080/10413200601113638CrossRefGoogle Scholar
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    Chatzitofis A, Zarpalas D, Filos D et al (2017) Technological module for unsupervised, personalized cardiac rehabilitation exercising. In: 2017 IEEE 41st annual computer software and applications conference (COMPSAC).  https://doi.org/10.1109/COMPSAC.2017.230
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    Claes J, Buys R, Avila A et al (2017) Validity of heart rate measurements by the Garmin Forerunner 225 at different walking intensities. J Med Eng Technol 41:480–485.  https://doi.org/10.1080/03091902.2017.1333166CrossRefGoogle Scholar
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via A Computer-Assisted System with Kinect Sensors and Wristband Heart Rate Monitors for Group Classes of Exercise-Based Rehabilitation | SpringerLink

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[Abstract] Suitability of Kinect for measuring whole body movement patterns during exergaming.

Abstract

Exergames provide a challenging opportunity for home-based training and evaluation of postural control in the elderly population, but affordable sensor technology and algorithms for assessment of whole body movement patterns in the home environment are yet to be developed.

The aim of the present study was to evaluate the use of Kinect, a commonly available video game sensor, for capturing and analyzing whole body movement patterns.

Healthy adults (n=20) played a weight shifting exergame under five different conditions with varying amplitudes and speed of sway movement, while 3D positions of ten body segments were recorded in the frontal plane using Kinect and a Vicon 3D camera system. Principal Component Analysis (PCA) was used to extract and compare movement patterns and the variance in individual body segment positions explained by these patterns. Using the identified patterns, balance outcome measures based on spatiotemporal sway characteristics were computed.

The results showed that both Vicon and Kinect capture >90% variance of all body segment movements within three PCs. Kinect-derived movement patterns were found to explain variance in trunk movements accurately, yet explained variance in hand and foot segments was underestimated and overestimated respectively by as much as 30%. Differences between both systems with respect to balance outcome measures range 0.3–64.3%.

The results imply that Kinect provides the unique possibility of quantifying balance ability while performing complex tasks in an exergame environment.

via Suitability of Kinect for measuring whole body movement patterns during exergaming – ScienceDirect

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[Abstract] MaLT – Combined Motor and Language Therapy Tool for Brain Injury Patients Using Kinect.

Abstract

BACKGROUND:

The functional connectivity and structural proximity of elements of the language and motor systems result in frequent co-morbidity post brain injury. Although rehabilitation services are becoming increasingly multidisciplinary and “integrated”, treatment for language and motor functions often occurs in isolation. Thus, behavioural therapies which promote neural reorganisation do not reflect the high intersystem connectivity of the neurologically intact brain. As such, there is a pressing need for rehabilitation tools which better reflect and target the impaired cognitive networks.

OBJECTIVES:

The objective of this research is to develop a combined high dosage therapy tool for language and motor rehabilitation. The rehabilitation therapy tool developed, MaLT (Motor and Language Therapy), comprises a suite of computer games targeting both language and motor therapy that use the Kinect sensor as an interaction device. The games developed are intended for use in the home environment over prolonged periods of time. In order to track patients’ engagement with the games and their rehabilitation progress, the game records patient performance data for the therapist to interrogate.

METHODS:

MaLT incorporates Kinect-based games, a database of objects and language parameters, and a reporting tool for therapists. Games have been developed that target four major language therapy tasks involving single word comprehension, initial phoneme identification, rhyme identification and a naming task. These tasks have 8 levels each increasing in difficulty. A database of 750 objects is used to programmatically generate appropriate questions for the game, providing both targeted therapy and unique gameplay every time. The design of the games has been informed by therapists and by discussions with a Public Patient Involvement (PPI) group.

RESULTS:

Pilot MaLT trials have been conducted with three stroke survivors for the duration of 6 to 8 weeks. Patients’ performance is monitored through MaLT’s reporting facility presented as graphs plotted from patient game data. Performance indicators include reaction time, accuracy, number of incorrect responses and hand use. The resultant games have also been tested by the PPI with a positive response and further suggestions for future modifications made.

CONCLUSION:

MaLT provides a tool that innovatively combines motor and language therapy for high dosage rehabilitation in the home. It has demonstrated that motion sensor technology can be successfully combined with a language therapy task to target both upper limb and linguistic impairment in patients following brain injury. The initial studies on stroke survivors have demonstrated that the combined therapy approach is viable and the outputs of this study will inform planned larger scale future trials.

KEYWORDS:

 

via MaLT – Combined Motor and Language Therapy Tool for Brain Injury Patients Using Kinect. – PubMed – NCBI

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[Abstract] Feasibility study of a serious game based on Kinect system for functional rehabilitation of the lower limbs

Summary

Introduction

Conventional functional rehabilitation costs time, money and effort for the patients and for the medical staff. Serious games have been used as a new approach to improve the performance as well as to possibly reduce medical cost in the future for cognitive rehabilitation and body balance control. The objective of this present work was to perform a feasibility study on the use of a new real-time serious game system for improving the musculoskeletal rehabilitation of the lower limbs.

Materials and methods

A basic functional rehabilitation exercise database was established with different levels of difficulties. A 3D virtual avatar was created and scaled to represent each subject-specific body. A portable and affordable Kinect sensor was used to capture real-time kinematics during each exercise. A specific data coupling process was developed. An evaluation campaign was established to assess the developed system.

Results

The squats exercise was the hardest challenge. Moreover, the performance of each functional rehabilitation exercise depended on the physiological profile of each participant. Our game system was clear and attractive for all functional rehabilitation exercises. All testing subjects felt motivated and secure when playing the rehabilitation game.

Discussion

The comparison with other systems showed that our system was the first one focusing on the functional rehabilitation exercises of the lower limbs.

Conclusions

Our system showed useful functionalities for a large range of applications (rehabilitation at home, sports training). Looking forward, new in-situation exercises will be investigated for specific musculoskeletal disorders.

via Feasibility study of a serious game based on Kinect system for functional rehabilitation of the lower limbs – ScienceDirect

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[ARTICLE] Overcome Acrophobia with the Help of Virtual Reality and Kinect Technology – Full Text PDF

Abstract

There are many people in this world who are feared of high places. In general, there are two types of people: the prior one is people that are afraid of height and the latter one is people who really cannot handle high places (i.e. acrophobia). The purpose of this research is to reduce acrophobia level of people. The methodology which is used in this research is experiment with the help of virtual reality to simulate virtual world of high places environment as the reality in the imagination of the user. The virtual environment helps the sufferer to reduce their fear of height in a safe and controllable environment. This research shows that virtual reality is able to mimic real high places and train the users to overcome their anxiety of high places. With virtual world, the users are able to confront their fear gradually based on the level progression in the virtual world. Thus, it gives the users more experience to handle their fear in the secured environment and gradually decrease their anxiety level of acrophobia.[…]

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Source: Overcome Acrophobia with the Help of Virtual Reality and Kinect Technology

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[Conference paper] Kushkalla: A Web-Based Platform to Improve Functional Movement Rehabilitation – Full Text

Abstract

Telerehabilitation is a growing alternative to traditional face-to-face therapy, which uses technological solutions to cover rehabilitation care in both clinical centers and in-home programs. However, the current telerehabilitation systems are limited to deliver a set of exercise programs for some specific locomotor disability, without including tools that allow a quantitative analysis of the rehabilitation progress, in real-time, as well as the medical condition of patients. This paper presents the design and development of a novel web-based platform, named “Kushkalla”, that allows to perform movement assessment for creating personalized home-based therapy routines, integrating hardware and software tools for a quantitative analysis of locomotor movements based on motion capture, preprocessing, monitoring, visualization, storage and analysis, in real-time. The platform combines two motion capture strategies, the Kinect-based and IMU-based motion capture. In addition, a set of 2D and 3D graphical models, virtual environments, based on WebGL technology, and videoconference module are included to allow the interaction between user and clinician for enhancing the capability of the clinician to direct rehabilitation therapies.

Introduction

According to the World Health Organization, at least 15% of world people could present musculoskeletal disabilities, which present difficulties to access appropriate management even in diagnosis, treatment or follow-up stages. Particularly, it is estimated that between 76% and 85% of disabled people have not accessed to treatment programs in developing countries [17]. Conventionally, when a musculoskeletal disability is diagnosed, a clinical specialist designs a specific functional rehabilitation program, according to the analysis of the strength, flexibility and other biomechanical aspects of the patient; then, a team of therapists is responsible for its execution and follow-up. Both diagnosis and follow-up require quantifying those biomechanical aspects in order to guarantee that the designed program is suitable for the patient. This workflow demands an important number of therapists and technologies, such as strength platforms, to ensure the quality of the rehabilitation program. Additionally, the patient location could be a major obstacle for this purpose. This is the case of some rehabilitation programs to restore functional movements of elderly people, which are constantly suffering locomotor impairment caused by aging. Thus, functional movement rehabilitation programs evaluate the movement patterns from each patient to establish what parts of the human body may be treated. An improper movement pattern or imbalances throughout the human body allow determining postural and motor issues, which are used to develop different rehabilitation programs by the therapist. Therefore, functional movement rehabilitation programs are able to rehabilitate the human body that is weak, tight or unbalance by using a combination of functional movement correction and classic rehabilitation exercises.

Recently, telerehabilitation has emerged as an alternative that allows to perform functional movement rehabilitation activities from the comfort of the patient location, which are monitored by the physician from the specialized medical center [14]. This is possible by the use of the Internet and emerging technologies such as inertial sensors, optical motion capture devices, robots, virtual reality environments, among others [4]. In general, telerehabilitation strategies can be classified as: telepresence-based rehabilitation, which are supported by videoconference tools that allow a continuous communication between patient and physician [3]; robotic-based rehabilitation, which uses autonomous robots or exoskeletons for guiding patient movements [7]; interactive-based rehabilitation, which uses interactive environments for motivating patient to perform exercises while playing [121521] and; rehabilitation based on a precision analysis, which provides movement analysis tools for supporting the physician decisions [11].

This paper describes the design and development of a novel web-based platform that integrates telepresence, interactive environments, and movement analysis tools, for providing the technology to carry out functional movement assessment and to create personalized home-based therapy routines. The proposed Web-based platform was developed on a service-oriented architecture (SOA), a client/server software design approach in which an application consists of software services and software service consumers that are provided between software components through several network communication protocols [16]. It is composed of two main software parts: a client and a cloud server components. Additionally, two applications conform the client component: the patient application, and the physician application. The patient application includes a bimodal human motion capture module that allows to integrate both a wearable inertial sensor system and a depth camera sensor (Kinect); a visualization module provided with a virtual environment with an interactive interface in which patient can see in two 3D avatars how an exercise must be executed and how they execute it; and an assistance module provided with a videoconference tool and videotutorials about the platform. The Physician application includes an exercise visualization module, synchronized with the patient interface, in which real-time patient movements are displayed, and a motion analysis module, which displays graphically the movement measurements generated by the analysis of captured data. Finally, the server component, implemented as a software as a service cloud component that it includes a web-server, a websocket server, a webRTC (web with Real-Time Communications) server, and relational and non-relational databases.

This paper is organized as follows. The next section presents a brief summary of related works. In the Sect. 3 the main hardware/software components of the proposed platform are described. Section 4 presents a preliminary evaluation that shows the reliability of the proposed architecture and finally, Sect. 5 presents the conclusions and discuss the future work.[…]

Continue —>  Kushkalla: A Web-Based Platform to Improve Functional Movement Rehabilitation | SpringerLink

Fig. 1. General framework of Kushkalla: Telerehabilitation platform

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[Abstract] Design and Test of a Closed-Loop FES System for Supporting Function of the Hemiparetic Hand Based on Automatic Detection Using the Microsoft Kinect Sensor

Abstract
This paper describes the design of a FES system automatically controlled in a closed loop using a Microsoft Kinect sensor, for assisting both cylindrical grasping and hand opening. The feasibility of the system was evaluated in real-time in stroke patients with hand function deficits. A hand function exercise was designed in which the subjects performed an arm and hand exercise in sitting position. The subject had to grasp one of two differently sized cylindrical objects and move it forward or backwards in the sagittal plane. This exercise was performed with each cylinder with and without FES support. Results showed that the stroke patients were able to perform up to 29% more successful grasps when they were assisted by FES. Moreover, the hand grasp-and-hold and hold-and-release durations were shorter for the smaller of the two cylinders. FES was appropriately timed in more than 95% of all trials indicating successful closed loop FES control. Future studies should incorporate options for assisting forward reaching in order to target a larger group of stroke patients.

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[Abstract] Motion Rehab AVE 3D: A VR-based exergame for post-stroke rehabilitation

Abstract

Background and objective

Recent researches about games for post-stroke rehabilitation have been increasing, focusing in upper limb, lower limb and balance situations, and showing good experiences and results. With this in mind, this paper presents Motion Rehab AVE 3D, a serious game for post-stroke rehabilitation of patients with mild stroke. The aim is offer a new technology in order to assist the traditional therapy and motivate the patient to execute his/her rehabilitation program, under health professional supervision.

Methods

The game was developed with Unity game engine, supporting Kinect motion sensing input device and display devices like Smart TV 3D and Oculus Rift. It contemplates six activities considering exercises in a tridimensional space: flexion, abduction, shoulder adduction, horizontal shoulder adduction and abduction, elbow extension, wrist extension, knee flexion, and hip flexion and abduction. Motion Rehab AVE 3D also report about hits and errors to the physiotherapist evaluate the patient’s progress.

Results

A pilot study with 10 healthy participants (61–75 years old) tested one of the game levels. They experienced the 3D user interface in third-person. Our initial goal was to map a basic and comfortable setup of equipment in order to adopt later. All the participants (100%) classified the interaction process as interesting and amazing for the age, presenting a good acceptance.

Conclusions

Our evaluation showed that the game could be used as a useful tool to motivate the patients during rehabilitation sessions. Next step is to evaluate its effectiveness for stroke patients, in order to verify if the interface and game exercises contribute into the motor rehabilitation treatment progress.

Source: Motion Rehab AVE 3D: A VR-based exergame for post-stroke rehabilitation – ScienceDirect

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