scholarly journals Comparison of Manipulative Indicators of Students and Therapists Using a Robotic Arm

2021 ◽  
Author(s):  
KOIKE Yuji ◽  
OKINO Akihisa ◽  
TAKEDA Kazuhisa ◽  
TAKANAMI Yasuhiro ◽  
Toyohiro Hamaguchi
Keyword(s):  
Elbow Joint ◽  
Muscle Tone ◽  
Peak Velocity ◽  
Movement Time ◽  
Analysis Of Covariance ◽  
Joint Movement ◽  
Extended Position ◽  
Tone Intensity ◽  
Training Schools ◽  
Education Of Students

Abstract Background: The purpose of this study was to clarify the motion therapy elements necessary for the education of students through comparison of the therapeutic motion techniques of therapists and students using an educational arm robot (Samothrace: SAMO) set with varying degrees of muscle tone pathology.Methods: The participants included eight therapists with more than five years of clinical experience and 25 fourth-year students from occupational therapy training schools who had completed their clinical practice. The therapeutic motion therapy task was a reciprocating exercise in which the elbow joint of SAMO was flexed from an extended position and then re-extended. This was performed three times for each of the three types of muscle tone intensities (mild, moderate, and severe), for a total of nine repetitions. The peak velocity, peak angle ratio, peak velocity time, and movement time were recorded using SAMO while the subjects performed the therapeutic motion therapy task. These data were compared using analysis of covariance. Results: The SAMO elbow joint kinematic data generated by therapists were significantly different than those of students for different muscle tones. It was clear from multiple comparisons that the therapeutic motion techniques of students were associated with higher peak velocity, smaller peak angle ratio, and shorter peak velocity time and movement time than those of therapists. Conclusion: The therapeutic motion techniques applied by the students in response to the muscle tone condition of the arm robot were different from those applied by therapists, suggesting that the students were not able to perform the therapeutic motion techniques in response to the degree of the muscle tone intensity in the same way that an expert could. Based on the results, when students learn therapeutic motion techniques, they should be taught to 1) deal with multiple muscle tone intensities and 2) reduce the speed of joint movement applied to the patient, extend the exercise time, and ensure maximum range of joint movement. These were the suggested guiding factors.

Comparison of Manipulative Indicators of Students and Therapists Using a Robotic Arm: A Feasibility Study

2021 ◽  
Vol 11 (20) ◽  
pp. 9403
Author(s):  
Koike Yuji ◽  
Okino Akihisa ◽  
Takeda Kazuhisa ◽  
Takanami Yasuhiro ◽  
Toyohiro Hamaguchi
Keyword(s):  
Elbow Joint ◽  
Muscle Tone ◽  
Peak Velocity ◽  
Movement Time ◽  
Analysis Of Covariance ◽  
Movement Speed ◽  
Joint Movement ◽  
Exercise Time ◽  
Kinematic Data ◽  
Extended Position

In this study, the motion therapy elements necessary for student education were clarified through comparison of the therapeutic motion techniques of therapists and students using an educational arm robot (Samothrace: SAMO). Eight therapists and 25 fourth-year students participated. The therapeutic motion therapy task was a reciprocating exercise in which the elbow joint of SAMO was flexed from an extended position and then re-extended. This was performed for three types of muscle tone intensities (mild, moderate, and severe), and the peak velocity, angle ratio, velocity time, and movement time were recorded using SAMO. These data were then compared using analysis of covariance. It was found that the SAMO elbow joint kinematic data generated by therapists differed significantly from those of students for different muscle tones. Multiple comparisons showed that the therapeutic motion techniques of students were associated with a higher peak velocity, smaller peak angle ratio, and shorter peak velocity time and movement time than those of the therapists. Thus, when students learn therapeutic motion techniques, they should be taught to (1) deal with multiple muscle tone intensities and (2) reduce the joint movement speed applied to the patient to extend the exercise time and ensure maximum joint movement range.

Movement Control Phases of Upper Body Coordination in Visually Guided Reach Movements

2009 ◽  
Vol 53 (12) ◽  
pp. 834-838
Author(s):  
Shin-Yuan Yu ◽  
Bernard J. Martin
Keyword(s):  
Motor Behavior ◽  
Peak Velocity ◽  
Movement Time ◽  
Movement Control ◽  
Human Movement ◽  
Upper Body ◽  
Movement Speed ◽  
Joint Movement ◽  
Feedback Information ◽  
Time To Peak

Coordination of human movement includes temporal and spatial aspects. Under the assumption that the implicit movement sequence of body segments may be associated with visual feedback information, the activation timing, time to peak velocity of the hand and sequencing of joint movements were investigated in this study. The results show that variations in movement time with target azimuth and distance fit a quadratic regression model. In addition, the time to peak velocity reveals a movement scaling property in the context of self-imposed movement speed. Finally, the sequencing of joint movement also varies with target azimuth and distance. These motor behavior properties and movement characteristics can be used to model human reach movement in a dynamic manner and to estimate task durations.

CONTINUOUS MOTION AND TIME-VARYING STIFFNESS ESTIMATION OF THE HUMAN ELBOW JOINT BASED ON SEMG

2019 ◽  
Vol 19 (05) ◽  
pp. 1950040 ◽  
Author(s):  
KEXIANG LI ◽  
XUAN LIU ◽  
JIANHUA ZHANG ◽  
MINGLU ZHANG ◽  
ZIMIN HOU
Keyword(s):  
Elbow Joint ◽  
Joint Stiffness ◽  
Muscle Stiffness ◽  
Time Varying ◽  
Joint Movement ◽  
Estimation Model ◽  
Unknown Parameters ◽  
Continuous Motion ◽  
Robotic Joints ◽  
Mean Square Errors

The flexibility of body joints plays an important role in daily life, particularly when performing high-precision rapid pose switching. Importantly, understanding the characteristics of human joint movement is necessary for constructing robotic joints with the softness of humanoid joints. A novel method for estimating continuous motion and time-varying stiffness of the human elbow joint was proposed in the current study, which was based on surface electromyography (sEMG). We used the Hill-based muscle model (HMM) to establish a continuous motion estimation model (CMEM) of the elbow joint, and the genetic algorithm (GA) was used to optimize unknown parameters. Muscle short-range stiffness (SRS) was then used to characterize muscle stiffness, and a joint kinetic equation was used to express the relationship between skeletal muscle stiffness and elbow joint stiffness. Finally, we established a time-varying stiffness estimation model (TVSEM) of the elbow joint based on the CMEM. In addition, five subjects were tested to verify the performance of the CMEM and TVSEM. The total average root-mean-square errors (RMSEs) of the CMEM with the optimal trials were 0.19[Formula: see text]rad and 0.21[Formula: see text]rad and the repeated trials were 0.24[Formula: see text]rad and 0.25[Formula: see text]rad, with 1.25-kg and 2.5[Formula: see text]kg-loads, respectively. The values of elbow joint stiffness ranged from 0–40[Formula: see text]Nm/rad for different muscle activities, which were estimated by the TVSEM.

scholarly journals Distinction of Students and Expert Therapists Based on Therapeutic Motions on a Robotic Device Using Support Vector Machine

2020 ◽  
Vol 40 (6) ◽  
pp. 790-797
Author(s):  
Koike Yuji ◽  
Suzuki Makoto ◽  
Okino Akihisa ◽  
Takeda Kazuhisa ◽  
Takanami Yasuhiro ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Exercise Therapy ◽  
Upper Limb ◽  
Peak Velocity ◽  
Movement Time ◽  
Elbow Flexion ◽  
Flexion Angle ◽  
Support Vector ◽  
Robot Arm ◽  
Clinical Practices

Abstract Purpose To clarify the feature values of exercise therapy that can differentiate students and expert therapists and use this information as a reference for exercise therapy education. Methods The participants were therapists with 5 or more years of clinical experience and 4th year students at occupational therapist training schools who had completed their clinical practices. The exercise therapy task included Samothrace (code name, SAMO) exercises implemented on the elbow joint based on the elbow flexion angle, angular velocity, and exercise interval recordings. For analyses and student/therapist comparisons, the peak flexion angle, peak velocity, and movement time were calculated using data on elbow angle changes acquired via SAMO. Subsequently, bootstrap data were generated to differentiate between the exercise therapy techniques adopted by therapists and students, and a support vector machine was used to generate four types of data combinations with the peak flexion angle, peak velocity, and movement time values. These data were used to estimate and compare the respective accuracies with the Friedman test. Results The peak flexion angles were significantly smaller in the case of students. Furthermore, the peak velocities were larger, the peak flexion angles were smaller, and the movement times were shorter compared with those of therapists. The combination of peak velocity and peak flexion angle yielded the highest diagnostic accuracies. Conclusion When students and therapists performed upper limb exercise therapy techniques based on the kinematics movement of a robot arm, the movement speeds and joint angles differed. The combination of peak velocity and peak flexion angle was the most effective classifier used for the differentiation of the abilities of students and therapists. The peak velocity and peak flexion angle of the therapist group can be used as a reference for students when they learn upper limb therapeutic exercise techniques.

Measuring poststroke spasticity

2000 ◽  
Vol 10 (1) ◽  
pp. 69-74 ◽  
Author(s):  
J. M. Gregson ◽  
A. K. Sharma
Keyword(s):  
Normal State ◽  
Stretch Reflex ◽  
Muscle Activation ◽  
Muscle Tone ◽  
Clinical Syndrome ◽  
Motor Disorder ◽  
Muscle Forces ◽  
Joint Movement ◽  
Stretch Reflexes ◽  
Reflex Action

What is spasticity?Spasticity is a well-recognized and potentially important clinical syndrome comprising inappropriate and involuntary high muscle tone. It has been variably defined, with debate still ongoing. Currently, the most widely accepted definition is that of Lance, stating that spasticity is ‘a motor disorder characterized by a velocity-dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks, resulting from hyper-excitability of the stretch reflex.’ Unfortunately, even this description does not fully encompass the multifactorial nature of spasticity, since resistance to movement, even in the normal state, is subject to varied contributors. These include patient volition, inertia, visco-elastic muscle forces and range of joint movement, as well as true muscle activation secondary to reflex action. In the real clinical world, it is often not possible to distinguish which of these features is/are dominant. Furthermore, spastic muscle undergoes physiopathological, rheologic change with stiffness, atrophy, fibrosis and finally contracture.

scholarly journals Parkinsonian Rigidity Shows Variable Properties Depending on the Elbow Joint Angle

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Takuyuki Endo ◽  
Toshimitsu Hamasaki ◽  
Ryuhei Okuno ◽  
Masaru Yokoe ◽  
Harutoshi Fujimura ◽  
...  
Keyword(s):  
Elbow Joint ◽  
Joint Angle ◽  
Muscle Tone ◽  
Full Range ◽  
Elbow Extension ◽  
Variable Properties ◽  
Elastic Coefficient ◽  
Significant Difference ◽  
Flexion And Extension ◽  
Elastic Coefficients

Parkinsonian rigidity has been thought to be constant through a full range of joint angle. The aim of this study was to perform a detailed investigation of joint angle dependency of rigidity. We first measured muscle tone at the elbow joint in 20 healthy subjects and demonstrated that an angle of approximately 60° of flexion marks the division of two different angle-torque characteristics. Then, we measured muscle tone at the elbow joint in 24 Parkinson’s Disease (PD) patients and calculated elastic coefficients in flexion and extension in the ranges of 10°–60° (distal) and 60°–110° (proximal). Rigidity as represented by the elastic coefficient in the distal phase of elbow joint extension was best correlated with the UPDRS rigidity score (r=0.77). A significant difference between the UPDRS rigidity score 0 group and 1 group was observed in the elastic coefficient in the distal phase of extension (P<0.0001), whereas no significant difference was observed in the proximal phase of extension and in each phase of flexion. Parkinsonian rigidity shows variable properties depending on the elbow joint angle, and it is clearly detected at the distal phase of elbow extension.

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