Performance evaluation of joint angles obtained by the Kinect v2

Wiedemann, Lukas; Planinc, Rainer; Nemec, Iris; Kampel, Martin

doi:10.1049/ic.2015.0142

Cited by 16 publications

(6 citation statements)

References 15 publications

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“…The Kinect V1 also provided a seated tracking mode that was conceived to simplify and optimize seated positions, which is not implemented in Kinect V2. A study revealed some limitations in detecting specific postures and body angles [ 53 ], but such angles are not investigated in this study. Authors did not notice remarkable difference between standing and seating while executing upper limb tasks, and the tracking was always adequate, considering that only upper limb data were considered.…”

Section: Methodsmentioning

confidence: 99%

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

Scano

Chiavenna

Malosio

et al. 2017

Applied Bionics and Biomechanics

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Background The increase of sanitary costs related to poststroke rehabilitation requires new sustainable and cost-effective strategies for promoting autonomous and dehospitalized motor training. In the Riprendo@Home and Future Home for Future Communities research projects, the promising approach of introducing low-cost technologies that promote home rehabilitation is exploited. In order to provide reliable evaluation of patients, a reference database of healthy people's performances is required and should consider variability related to healthy people performances. Methods 78 healthy subjects performed several repetitions of daily-life gestures, the reaching movement (RM) and hand-to-mouth (HtMM) movement with both the dominant and nondominant upper limbs. Movements were recorded with a Kinect V2. A synthetic biomechanical protocol based on kinematical, dynamical, and motor control parameters was used to assess motor performance of the healthy people. The investigation was conducted by clustering participants depending on their limb dominancy (right/left), gender (male/female), and age (young/middle/senior) as sources of variability. Results Results showed that limb dominancy has minor relevance in affecting RM and HtMM; gender has relevance in affecting the HtMM; age has major effect in affecting RM and HtMM. Conclusions An investigation of healthy subjects' upper limb performances during daily-life gestures was performed with the Kinect V2 sensor. Findings will be the basis for a database of normative data for neurological patients' motor evaluation.

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Section: Methodsmentioning

confidence: 99%

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

Scano

Chiavenna

Malosio

et al. 2017

Applied Bionics and Biomechanics

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“… Skeletal model provided by the Software Development Kit (SDK) consisting of the 3D locations of 25 joints [ 37 ]. …”

Section: Figurementioning

confidence: 99%

A Kinect-Based Interactive System for Home-Assisted Active Aging

Muñoz¹,

Mollineda

Pla

2021

Sensors

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Virtually every country in the world is facing an unprecedented challenge: society is aging. Assistive technologies are expected to play a key role in promoting healthy lifestyles in the elderly. This paper presents a Kinect-based interactive system for home-assisted healthy aging, which guides, supervises, and corrects older users when they perform scheduled physical exercises. Interactions take place in gamified environments with augmented reality. Many graphical user interface elements and workflows have been designed considering the sensory, physical and technological shortcomings of the elderly, adapting accordingly the interaction methods, graphics, exercises, tolerance margins, physical goals, and scoring criteria. Experiments involved 57 participants aged between 65 and 80 who performed the same physical routine six times during 15 days. After each session, participants completed a usability survey. Results provided significant evidence that support (1) the effectiveness of the system in assisting older users of different age ranges, (2) the accuracy of the system in measuring progress in physical achievement of the elderly, and (3) a progressive acceptance of the system as it was used. As a main conclusion, the experiments verified that despite their poor technological skills, older people can adapt positively to the use of an interactive assistance tool for active aging if they experience clear benefits.

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“…Devices based on RGBdepth sensors, such as the Kinect (Microsoft), with embedded skeleton tracking algorithms, are nowadays available [42,8]. Yet, the Kinect was shown relevant for general purpose applications, where accuracy and speed are less crucial, and is still considered as not reliable and accurate enough for quantifying human motion (RMSD < 10deg) [104]. More recently, marker-less MCSs based on an RGB camera and a machine learning algorithm were applied to much further challenging scenes with multiple persons tracking [105,106].…”

Section: Marker-less Systemsmentioning

confidence: 99%

Toward an Affordable Multi-Modal Motion Capture System Framework for Human Kinematics and Kinetics Assessment

Mallat

Bonnet

Khalil

et al. 2018

Biosystems &Amp; Biorobotics

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Quantifying human motor act starts with measuring and estimating kinematics and dynamics variables as accurately as possible. Monitoring human motion has a wide array of applications in functional rehabilitation, orthopaedics, sports, assistive robotics or industrial ergonomics. Today's motion capture systems usually refer to stereophotogrammetric systems and laboratory-grade force-plate that are accurate but also costly, require expert skills, and are not portable. Recently, the use of affordable sensors for human motion estimation, such as Inertial Measurement Unit or RGB-Depth camera(s), has been the subject of numerous studies. Despite their great potential to be used outside of the laboratory, these systems still suffer from limited accuracy, mainly due to inherent IMU drift and visual occlusions, and the joint kinematics and kinetics estimates are still difficult to be estimated. These drawbacks might explain why such systems are rarely used in common clinical applications or for in-home rehabilitation programs. In this context, this thesis deals with the development of a new affordable motion capture system capable of estimating accurately human 3D joint state. Unlike previous studies based on either visual or inertial sensors, the proposed approach consists in combining data from newly designed visual-inertial sensors. The system is also making use of new practical calibration methods, which do not require any external equipment while remaining very affordable. All sensors data are fused into a constrained extended Kalman filter that takes advantage of the biomechanics of the human body and of the investigated tasks to improve significantly joint state estimate. This is done by incorporating different types of constraints, such as joint limits, rigid-body and soft joint constraints, as well as modelling the temporal evolution of joint trajectories and/or sensors random bias. The system's ability to estimate accurate 3D joint kinematics has been validated through various case studies of daily life activities for upper-arm and treadmill gait. Two different prototypes with different sensors count and configurations have been investigated. Experiments conducted with several healthy subjects showed very satisfactory results when compared to a gold standard motion capture system. Overall, the average RMS difference between the two systems was below 4deg. This was also the case when a reduced number of sensors was used for gait analysis. This system was also used for the dynamics identification of a viii lower-limbs human-exoskeleton system. As a result, an error below 6% was observed when comparing estimated and measured external ground reaction force and moments. Finally, beyond these validations, a dynamics assessment framework has been proposed with the aim of selecting an optimal human-exoskeleton dynamic model that is the best trade-off between the accuracy of kinetic estimation, i.e., joint torque, and simplicity of modelling. To this end, the proposed framework consists in quantifying the independent con...

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Performance evaluation of joint angles obtained by the Kinect v2

Cited by 16 publications

References 15 publications

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

A Kinect-Based Interactive System for Home-Assisted Active Aging

Toward an Affordable Multi-Modal Motion Capture System Framework for Human Kinematics and Kinetics Assessment

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