scholarly journals Quantitative Assessment of ADL: A Pilot Study of Upper Extremity Reaching Tasks

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Saiyi Li ◽  
Pubudu N. Pathirana ◽  
Mary P. Galea ◽  
Goetz Ottmann ◽  
Fary Khan
Keyword(s):  
Upper Extremity ◽  
Approximate Entropy ◽  
Microsoft Kinect ◽  
Human Observer ◽  
Movement Trajectory ◽  
Body Parts ◽  
Reaching Task ◽  
Reaching Tasks ◽  
Classification Tool ◽  
High Degree

Effective telerehabilitation technologies enable patients with certain physiological disabilities to engage in rehabilitative exercises for performing Activities of Daily Living (ADLs). Therefore, training and assessment scenarios for the performance of ADLs are vital for the promotion for telerehabilitation. In this paper we investigate quantitatively and automatically assessing patient’s kinematic ability to perform functional upper extremity reaching tasks. The shape of the movement trajectory and the instantaneous acceleration of kinematically crucial body parts, such as wrists, are used to compute the approximate entropy of the motions to represent stability (smoothness) in addition to the duration of the activity. Computer simulations were conducted to illustrate the consistency, sensitivity and robustness of the proposed method. A preliminary experiment with kinematic data captured from healthy subjects mimicking a reaching task with dyskinesia showed a high degree of correlation (Cohen’s kappa 0.85 withp<0.05) between a human observer and the proposed automatic classification tool in terms of assigning the datasets to various levels to represent the subjects’ kinematic abilities to perform reaching tasks. This study supported the use of Microsoft Kinect to quantitatively evaluate the ability of individuals with involuntary movements to perform an upper extremity reaching task.

scholarly journals A deep learning method for automatic segmentation of the bony orbit in MRI and CT images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jared Hamwood ◽  
Beat Schmutz ◽  
Michael J. Collins ◽  
Mark C. Allenby ◽  
David Alonso-Caneiro
Keyword(s):  
Deep Learning ◽  
Human Performance ◽  
Automatic Segmentation ◽  
Ct Images ◽  
Human Observer ◽  
In Series ◽  
Magnetic Resonance Imaging Mri ◽  
High Degree ◽  
Orbital Region ◽  
Ct And Mri

AbstractThis paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two different image modalities: magnetic resonance imaging (MRI) and computed tomography (CT). The method, based on a deep learning architecture, uses two fully convolutional neural networks in series followed by a graph-search method to generate a boundary for the orbit. When compared to human performance for segmentation of both CT and MRI data, the proposed method achieves high Dice coefficients on both orbit and background, with scores of 0.813 and 0.975 in CT images and 0.930 and 0.995 in MRI images, showing a high degree of agreement with a manual segmentation by a human expert. Given the volumetric characteristics of these imaging modalities and the complexity and time-consuming nature of the segmentation of the orbital region in the human skull, it is often impractical to manually segment these images. Thus, the proposed method provides a valid clinical and research tool that performs similarly to the human observer.

scholarly journals Effects of Seat Cushion Material on Center of Pressure and Movement Trajectory during a Reaching Task

2019 ◽  
Vol 15 (1) ◽  
pp. 85-92
Author(s):  
Takeshi Kodama ◽  
Yuji Nakamura ◽  
Sonomi Nakajima ◽  
Kenichi Kamoshita ◽  
Yasuhito Sengoku
Keyword(s):  
Center Of Pressure ◽  
Movement Trajectory ◽  
Reaching Task ◽  
Seat Cushion

Vojta-Therapy

2021 ◽  
pp. 383-398
Author(s):  
Muhammad Hassan Khan ◽  
Marcin Grzegorzek
Keyword(s):  
Template Matching ◽  
Movement Pattern ◽  
Microsoft Kinect ◽  
Support Vector ◽  
Therapy Process ◽  
Body Parts ◽  
External Stimulation ◽  
Kinect Camera ◽  
Specific Stimulation ◽  
The Given

This paper proposed a novel computer vision-based framework to recognize the accurate movements of a patient during the Vojta-therapy. Vojta-therapy is a useful technique for the physical and mental impairments in humans. During the therapy, a specific stimulation is given to the patients to cause the patient's body to perform certain reflexive pattern movements. The repetition of this stimulation ultimately makes available the previously blocked connections between the spinal cord and brain, and after a few sessions, patients can perform these movements without any external stimulation. In this paper the authors propose an automatic method for patient detection and recognition of specific movements in his/her various body parts during the therapy process, using Microsoft Kinect camera. The proposed method works in three steps. In the first step, a robust template matching based algorithm is exploited for patient's detection using his/her head location. Second, several features are computed to capture the movements of different body parts during the therapy process. Third, in the classification stage, a multi-class support vector machine (mSVM) is used to classify the accurate movements of patient. The classification results ultimately reveal the correctness of the given treatment. The proposed algorithm is evaluated on the authors' challenging dataset, which was collected in a children hospital. The detection and classification results show that the proposed method is highly useful to recognize the correct movement pattern either in hospital or in-home therapy systems.

scholarly journals The effects of motor modularity on performance, learning and generalizability in upper-extremity reaching: a computational analysis

2020 ◽  
Vol 17 (167) ◽  
pp. 20200011
Author(s):  
Mazen Al Borno ◽  
Jennifer L. Hicks ◽  
Scott L. Delp
Keyword(s):  
Upper Extremity ◽  
Realistic Model ◽  
Computational Time ◽  
Muscle Synergies ◽  
Performance Deficits ◽  
Reaching Task ◽  
Learning Rates ◽  
The Central Nervous System ◽  
The Rich ◽  
Low Dimensional

It has been hypothesized that the central nervous system simplifies the production of movement by limiting motor commands to a small set of modules known as muscle synergies. Recently, investigators have questioned whether a low-dimensional controller can produce the rich and flexible behaviours seen in everyday movements. To study this issue, we implemented muscle synergies in a biomechanically realistic model of the human upper extremity and performed computational experiments to determine whether synergies introduced task performance deficits, facilitated the learning of movements, and generalized to different movements. We derived sets of synergies from the muscle excitations our dynamic optimizations computed for a nominal task (reaching in a plane). Then we compared the performance and learning rates of a controller that activated all muscles independently to controllers that activated the synergies derived from the nominal reaching task. We found that a controller based on synergies had errors within 1 cm of a full-dimensional controller and achieved faster learning rates (as estimated from computational time to converge). The synergy-based controllers could also accomplish new tasks—such as reaching to targets on a higher or lower plane, and starting from alternative initial poses—with average errors similar to a full-dimensional controller.

scholarly journals Distinct population code for movement kinematics and changes of ongoing movements in human subthalamic nucleus

2020 ◽  
Author(s):  
Dennis London ◽  
Arash Fazl ◽  
Kalman Katlowitz ◽  
Marisol Soula ◽  
Michael H Pourfar ◽  
...  
Keyword(s):  
Subthalamic Nucleus ◽  
Action Plan ◽  
Field Potential ◽  
Neural Code ◽  
Neuronal Firing ◽  
Movement Trajectory ◽  
Movement Kinematics ◽  
Critical Test ◽  
Reaching Task ◽  
Basal Ganglia Structures

AbstractThe subthalamic nucleus (STN) is theorized to globally suppress movement through connections with downstream basal ganglia structures. Current theories are supported by increased STN activity when subjects withhold an uninitiated action plan, but a critical test of these theories requires studying STN responses when an ongoing action is replaced with an alternative. Here, we perform this test using an extended reaching task with instructions to switch movement trajectory mid-action. We show that STN activity decreases during action switches, contrary to prevalent theories. Further, beta oscillations in the local field potential in STN, which are associated with movement inhibition do not show increased power or entraining of neuronal firing during switches. We report an inhomogeneous population neural code in STN, with one sub-population encoding movement kinematics and direction and another encoding unexpected action switches. We suggest an elaborate neural code in STN that contributes to planning actions and changing the plans.

scholarly journals Optimization of Electro-Discharge Texturing Parameters for Steel Sheets’ Finishing Rollers

Materials ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1223
Author(s):  
Emil Evin ◽  
Miroslav Tomáš ◽  
Jozef Kmec
Keyword(s):  
Body Parts ◽  
Peak Voltage ◽  
Aluminum Sheets ◽  
Heat Treated ◽  
Output Characteristics ◽  
High Degree ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
The Impact ◽  
Peak Count

Exterior car-body parts are made of steel or aluminum sheets. Their formability and appearance after painting depends not only on the mechanical properties but also on their surface texture. The surface roughness characteristics, the roughness average Ra and the peak count Pc per centimeter depend on the texture of rolling mill’s finishing rollers, their wear and the degree of removal by the rolling mill. The research was carried out on heat-treated finishing rollers on the surface of which a controlled texture was created by changing the electro-discharge texturing (EDT) parameters. Parameters and the number of electro-discharge texturing experiments were optimized using full four-factor experiment techniques at the upper and lower levels of the parameters in the form of 24. The significance of the impact of individual EDT parameters and their interactions was identified based on the variance results. The ANOVA variance analysis results confirmed that the roughness Ra and the peak count Pc depend primarily on peak current (Ip), discharge peak voltage (Up), pulse on time (Pont) and pulse off time (Pofft). Optimization of the effect of the above parameters on the target roughness RaT,FR values and the peak count PcT,FR of finishing rollers was performed by the response surface methodology (RSM). Obtained regression models describe relationships between the input parameters of the electro-discharge texturing of finishing rollers and the output characteristics of the RaT,FR and the PcT,FR texture to a very high degree. The reliability of the electro-discharge texturing process of working rollers was assessed using the process capability index Cpk.

scholarly journals Long-Range Temporal Correlations, Multifractality, and the Causal Relation Between Neural Inputs and Movements

2011 ◽  
Author(s):  
Jianbo Gao ◽  
Yi Zheng ◽  
Jing Hu
Keyword(s):  
Factor Analysis ◽  
Long Range ◽  
Multifractal Analysis ◽  
Causal Relation ◽  
Fano Factor ◽  
Fluctuation Analysis ◽  
Movement Trajectory ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Reaching Task ◽  
Temporal Correlations

Understanding the causal relation between neural inputs and movements is very important for the success of brain machine interfaces (BMIs). In this study, we perform systematic statistical and information theoretical analysis of neuronal firings of 104 neurons, and employ three different types of fractal and multifractal techniques (including Fano factor analysis, multifractal detrended fluctuation analysis (MF-DFA), and wavelet multifractal analysis) to examine whether neuronal firings related to movements may have long-range temporal correlations. We find that MF-DFA and wavelet multifractal analysis (but not Fano factor analysis) clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a “re-setting” effect at the start of each reaching task. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses.

scholarly journals A virtual reality tool for measuring and shaping trunk compensation for persons with stroke: Design and initial feasibility testing

2019 ◽  
Vol 6 ◽  
pp. 205566831882367
Author(s):  
Matthew H Foreman ◽  
Jack R Engsberg
Keyword(s):  
Virtual Reality ◽  
Upper Extremity ◽  
Computer Games ◽  
Microsoft Kinect ◽  
Future Research ◽  
High Dose ◽  
Trunk Flexion ◽  
Movement Kinematics ◽  
Small Cohort ◽  
Motor Improvement

Background: Compensatory movement, such as flexing the trunk during reaching, may negatively affect motor improvement during task-based practice for persons with stroke. Shaping, or incrementally decreasing, the amount of compensation used during rehabilitation may be a viable strategy with methods using virtual reality. Methods: A virtual reality tool was designed to (1) monitor upper extremity movement kinematics with an off-the-shelf motion sensor (Microsoft Kinect V2), (2) convert movements into control of widely available computer games, and (3) provide real-time feedback to shape trunk compensation. This system was tested for feasibility by a small cohort of participants with chronic stroke ( n = 5) during a 1-h session involving 40 min of virtual reality interaction. Outcomes related to repetitions, compensation, movement kinematics, usability, motivation, and sense of presence were collected. Results: Participants achieved a very high dose of reaching repetitions (461 ± 184), with an average of 81% being successful and 19% involving compensatory trunk flexion. Participants rated the system as highly usable, motivating, engaging, and safe. Conclusions: VRShape is feasible to use as a tool for increasing repetition rates, measuring and shaping compensation, and enhancing motivation for upper extremity therapy. Future research should focus on software improvements and investigation of efficacy during a virtual reality-based motor intervention.

scholarly journals Epidemiology of Injuries in National Collegiate Athletic Association Men's Baseball: 2014–2015 Through 2018–2019

2021 ◽  
Vol 56 (7) ◽  
pp. 742-749
Author(s):  
Adrian J. Boltz ◽  
Jacob R. Powell ◽  
Hannah J. Robison ◽  
Sarah N. Morris ◽  
Christy L. Collins ◽  
...  
Keyword(s):  
Upper Extremity ◽  
National Collegiate Athletic Association ◽  
Injury Rate ◽  
Injury Surveillance ◽  
Surveillance Program ◽  
Body Parts ◽  
Injury Rates ◽  
Injury Characteristics ◽  
Collegiate Baseball ◽  
Rate Ratios

Context The National Collegiate Athletic Association has supported men's baseball championships since 1947. Since its inception, the number of participating teams and athletes has considerably expanded. Background Frequently conducting injury surveillance of collegiate baseball athletes is essential for identifying developing temporal patterns. Methods Exposure and injury data collected in the National Collegiate Athletic Association Injury Surveillance Program during 2014–2015 through 2018–2019 were analyzed. Injury counts, rates, and proportions were used to describe injury characteristics; injury rate ratios were used to examine differential injury rates. Results The overall injury rate was 3.16 per 1000 athlete-exposures. The preseason injury rate was significantly higher than the regular season injury rate. The most commonly injured body parts were shoulder (16.1%), arm or elbow (16%), and hand or wrist (13.9%). The most reported specific injury was hamstring tear (7.9%). Conclusions The findings of this study aligned with previous studies—most injuries were due to noncontact and overuse mechanisms, less than one-half of injuries were related to upper extremity body parts, and one-third of all injuries were reported among pitchers.

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