Using an accelerometer for analyzing a reach-to-grasp movement after stroke

Michaelsen, Stella Maris; Gomes, Raquel Pinheiro; Marques, Aline Perão; Rodrigues, Letí­cia Cardoso; Borges, Noé Gomes; Cláudino, Renato; Santos, Márcio Aurélio Líns dos

doi:10.1590/s1980-65742013000400012

Cited by 10 publications

(5 citation statements)

References 32 publications

(27 reference statements)

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“…Quantitative kinematic analysis has commonly utilized acceleration and time-to-peak acceleration (TPA) to evaluate movement patterns in human and animal models because it provides accurate information about spatiotemporal parameters [15]. Linear regression analysis was computed to determine the validity and test-retest reliability of the robotic horse and real horses's acceleration data and resultant acceleration data collected.…”

Section: Discussionmentioning

confidence: 99%

Comparison between the robo-horse and real horse movements for hippotherapy

Park

Shurtleff

Engsberg

et al. 2014

Bio-Medical Materials and Engineering

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While the novel robotic hippotherapy system has gradually gained clinical application for therapeutic intervention on postural and locomotor control in individuals with neurological or musculoskeletal impairments, the system's validity and reliability for the robotic hippotherapy system has not been well established. The objective of the current study was to investigate the validity and test-retest reliability of the robotic hippotherapy system by comparing with real horse movements. The 3-axis accelerometer sensors attached on the robotic and real horse saddles were used to collect 3-dimensional acceleration data at a preferred walking velocity. Linear regression analysis showed an excellent correlation in the time-topeak acceleration (TPA) (R 2 =0.997), but little correlation in X-axis acceleration between the real and robotic horses (R 2 =0.177), thus confirming consistent time control and a certain degree of variability between the robotic and real horse movements. The mean resultant accelerations for a real horse and robotic horse were 3.22 m/s 2 and 0.67 m/s 2 , respectively, accounting for almost five times greater acceleration in the real horse than the robotic horse.

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Section: Discussionmentioning

confidence: 99%

Comparison between the robo-horse and real horse movements for hippotherapy

Park

Shurtleff

Engsberg

et al. 2014

Bio-Medical Materials and Engineering

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“…The use of accelerometers in this study is very significant, especially considering that previous studies have used accelerometers for monitoring physical activity or wheelchair movement 17 , 18 ) . Accelerometers make it easy to measure variables such as movement time and peak velocity, and it is also easy to obtain data such as EMG records 7 , 19 ) . In the future, we must consider the appropriate backrest thickness for wheelchair users, and assessment methods using accelerometers can provide feedback for appropriate wheelchair measurement for wheelchair users.…”

Section: Discussionmentioning

confidence: 99%

A study on effects of backrest thickness on the upper arm and trunk muscle load during wheelchair propulsion

Lee

Yoo

2016

J Phys Ther Sci

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[Purpose] The purpose of this study was to investigate the effects of the thickness of a wheelchair backrest provided for support and comfort on upper arm and trunk muscle load during wheelchair propulsion by using accelerometers. [Subjects and Methods] The Fourteen healthy participants were enrolled in this study. The study compared effects of three backrest conditions including no pad, a 3-cm-thick lumbar pad, and a 6-cm-thick lumbar pad. The instruments used for measurement were used two accelerometers. The participants were asked to propel their wheelchairs, which had been equipped with two accelerometers, 30 times. [Results] The intensity of muscle movement with the 3-cm-thick lumbar pad was significantly lower than the intensities with no lumbar pad and the 6-cm-thick lumbar pad. The muscle intensity did not differ significantly between the no pad and 6-cm-thick lumbar pad conditions. [Conclusion] An appropriately thick backrest has good effects on upper arm and trunk muscles during wheelchair propulsion. In the future, we must consider the appropriate backrest thickness for providing wheelchair users with a comfortable wheelchair.

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“…The result of the measurement was used to determine the appropriate exercise [8]. A more specific study on the ability of fingers of the patients was done by Michaelsen et al They used the accelerometer to train reachto-grasp motion for chronical hemiparesis, by putting it under the forearms [9].…”

Section: Introductionmentioning

confidence: 99%

Accelerometer-Based Recorder of Fingers Dynamic Movements for Post-Stroke Rehabilitation

Dwiputra¹,

Achmad²,

Faridah³

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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Stroke is a disease that currently attracts more attention in Indonesia according to the statistics provided by the Ministry of Health of the Republic of Indonesia. This research was motivated by the shortage of physiotherapists which can not catch the increasing number of stroke patients. The therapy becomes less effective and less efficient since each therapist must handle too many patients during his/her work hours. This research has developed a device prototype that can help the therapy to measure and monitor patient exercise, especially at the final stage of rehabilitation when the patient gets therapy to move actively. The angle of the moving body parts that can represent the ability of patient motion was measured using accelerometers. The developed prototype was in the form of a glove, equipped with an Arduino Nano and two accelerometer modules, that measures the motion of the thumb and index finger. The device was calibrated and tested to determine the characteristics of the sensors. This test showed that the gloves prototype had an accuracy of 95,8% and precision of 99,6%. The application of the prototype was carried out on four types of finger movements, namely thumb abduction-adduction, thumb flexion-extension, finger flexion-hyperextension, and finger abductionadduction. The prototype was also tested for its ability to work in variations of direction and position of the hand.

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Using an accelerometer for analyzing a reach-to-grasp movement after stroke

Cited by 10 publications

References 32 publications

Comparison between the robo-horse and real horse movements for hippotherapy

Comparison between the robo-horse and real horse movements for hippotherapy

A study on effects of backrest thickness on the upper arm and trunk muscle load during wheelchair propulsion

Accelerometer-Based Recorder of Fingers Dynamic Movements for Post-Stroke Rehabilitation

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