scholarly journals A Review on Wearable Technologies for Tremor Suppression

2021 ◽  
Vol 12 ◽  
Author(s):  
Julio S. Lora-Millan ◽  
Gabriel Delgado-Oleas ◽  
Julián Benito-León ◽  
Eduardo Rocon
Keyword(s):  
Side Effects ◽  
Upper Limb ◽  
Daily Living ◽  
Body Part ◽  
Wearable Technologies ◽  
Oscillatory Movement ◽  
Tremor Suppression ◽  
Management Paradigms ◽  
Validation Procedure ◽  
Hazardous Procedure

Tremor is defined as a rhythmic, involuntary oscillatory movement of a body part. Although everyone exhibits a certain degree of tremor, some pathologies lead to very disabling tremors. These pathological tremors constitute the most prevalent movement disorder, and they imply severe difficulties in performing activities of daily living. Although tremors are currently managed through pharmacotherapy or surgery, these treatments present significant associated drawbacks: drugs often induce side effects and show decreased effectiveness over years of use, while surgery is a hazardous procedure for a very low percentage of eligible patients. In this context, recent research demonstrated the feasibility of managing upper limb tremors through wearable technologies that suppress tremors by modifying limb biomechanics or applying counteracting forces. Furthermore, recent experiments with transcutaneous afferent stimulation showed significant tremor attenuation. In this regard, this article reviews the devices developed following these tremor management paradigms, such as robotic exoskeletons, soft robotic exoskeletons, and transcutaneous neurostimulators. These works are presented, and their effectiveness is discussed. The article also evaluates the different metrics used for the validation of these devices and the lack of a standard validation procedure that allows the comparison among them.

Theoretical Development and Experimental Validation of an Adaptive Controller for Tremor Suppression at Musculoskeletal Level

2013 ◽  
Author(s):  
Behzad Taheri ◽  
David Case ◽  
Edmond Richer
Keyword(s):  
Body Part ◽  
Adaptive Controller ◽  
Theoretical Development ◽  
Pneumatic Cylinder ◽  
Medical Treatments ◽  
Non Invasive ◽  
Oscillatory Movement ◽  
Tremor Suppression ◽  
Tremor Frequency ◽  
Intentional Motion

Tremor is a rhythmical and involuntary oscillatory movement of a body part. Mechanical loading via wearable exoskeletons is a non-invasive tremor suppression alternative to medical treatments. In this approach, the challenge is attenuating the tremor without affecting the patient’s intentional motion. An adaptive tremor suppression algorithm was designed to estimate and restrict motion within the tremor frequency band. An experimental setup was designed and developed to simulate the dynamics of a human arm joint with intentional and tremorous motion. The required orthotic suppressive force was applied via a pneumatic cylinder. The algorithm was implemented with a real-time controller and experimental results show tracking of the tremor frequency and a 97% reduction of tremor amplitude at the fundamental frequency.

scholarly journals A novel framework for designing a multi-DoF prosthetic wrist control using machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chinmay P. Swami ◽  
Nicholas Lenhard ◽  
Jiyeon Kang
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Upper Limb ◽  
Daily Living ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Random Forest Regression ◽  
Prosthetic Devices ◽  
Upper Limb Function ◽  
The Neural Network

AbstractProsthetic arms can significantly increase the upper limb function of individuals with upper limb loss, however despite the development of various multi-DoF prosthetic arms the rate of prosthesis abandonment is still high. One of the major challenges is to design a multi-DoF controller that has high precision, robustness, and intuitiveness for daily use. The present study demonstrates a novel framework for developing a controller leveraging machine learning algorithms and movement synergies to implement natural control of a 2-DoF prosthetic wrist for activities of daily living (ADL). The data was collected during ADL tasks of ten individuals with a wrist brace emulating the absence of wrist function. Using this data, the neural network classifies the movement and then random forest regression computes the desired velocity of the prosthetic wrist. The models were trained/tested with ADLs where their robustness was tested using cross-validation and holdout data sets. The proposed framework demonstrated high accuracy (F-1 score of 99% for the classifier and Pearson’s correlation of 0.98 for the regression). Additionally, the interpretable nature of random forest regression was used to verify the targeted movement synergies. The present work provides a novel and effective framework to develop an intuitive control for multi-DoF prosthetic devices.

scholarly journals Examination of Kinect’s Torso PCA Model for Planar Activities Assessment after Stroke

2019 ◽  
Vol 8 (12S2) ◽  
pp. 476-482
Keyword(s):  
Motion Capture ◽  
Upper Limb ◽  
Daily Living ◽  
Hand Movement ◽  
Three Dimensional ◽  
Principal Component ◽  
Stroke Patients ◽  
Joint Coordination ◽  
Arm Transport ◽  
Statistical Results

Compensatory movement after stroke occurred when inter-joint coordination between arm and forearm for the purpose of arm transport becomes limited due to the weaknesses of the upper limb after stroke. This limitation causes an inefficiency of hand movement to perform the activity of daily living (ADL). Previous work has shown the possibility of using Kinect to assess torso compensation in typical assessment of upper limb movement in a stroke-simulated setting using a Torso Principal Component Analysis (PCA) Model. This research extends the study into evaluating Torso PCA Model in terms of orientation angles of the torso in three dimensional when performing planar activities namely circle tracing and point-topoint tracing. The orientation angles were compared to the outcome of the measurement from a standard motion capture system and Kinect’s intrinsic chest orientation angles. Based on the statistical results, Torso PCA model is concurrently valid with the clinically accepted measures of torso orientation and can be used further to analyze torso compensation in stroke patients.

scholarly journals Evaluating the Contourhook—help or hindrance?

1986 ◽  
Vol 10 (2) ◽  
pp. 99-102
Author(s):  
V. E. Angliss
Keyword(s):  
Activities Of Daily Living ◽  
Upper Limb ◽  
Daily Living ◽  
World Congress ◽  
Terminal Device ◽  
Development Unit

A new Contourhook terminal device was introduced to the Central Development Unit (CDU) in Australia through the therapist attending the exhibit at the ISPO World Congress, London, September, 1983. Ten upper limb amputees, who were experienced prosthetic users were selected for the evaluation. The patients were asked to attend the CDU to perform selected activities; 7 activities were designed to simulate hand prehension and 17 were bimanual activities of daily living. The activities were performed using the conventional split hook terminal device. The same activities were repeated using the Contourhook terminal device. Performances and patients' comments were recorded. In general the Contourhook was found to compare unfavourably with conventional terminal devices, aspects of the brochure were misleading and all patients preferred their previously worn terminal device.

scholarly journals A COMPARATIVE STUDY OF ROPIVACAINE VERSUS ROPIVACAINE WITH DEXMEDETOMIDINE AS AN ADJUVANT IN SUPRACLAVICULAR BRACHIAL PLEXUS BLOCK

2021 ◽  
pp. 138-142
Author(s):  
Deba Gopal Pathak ◽  
Dipanjali Nath
Keyword(s):  
Side Effects ◽  
Brachial Plexus ◽  
Upper Limb ◽  
Local Anesthetic ◽  
Brachial Plexus Block ◽  
Onset Time ◽  
Sensory Blockade ◽  
Suitable Alternative ◽  
Supraclavicular Brachial Plexus Block ◽  
Plexus Block

BACKGROUND : Supraclavicular approach to brachial plexus block is a versatile and reliable regional anesthesia technique and a suitable alternative to general anesthesia for upper limb surgical procedures. Ropivacaine , a long acting local anesthetic, with less tendency for neurotoxicity and cardiotoxicity is a great local anesthetic for the procedure. Use of adjuvant Dexmedetomidine , a potent alpha 2 adrenoreceptor agonist improves the quality of anesthesia as well as intra-operative and post-operative analgesia while maintaining haemodynamic stability, arousable sedation and mild respiratory depression. MATERIALS AND METHODS: Eighty patients aged between 18 and 60 years with ASA grade I or II posted for elective upper limb surgeries were included in the study and were randomly divided into 2 groups with forty patients in each. Group A received 0.5% ropivacaine (31 mL) and Group B received 0.5% ropivacaine + dexmedetomidine 1microgram/kg (31mL). Both groups were compared for onset time and duration of sensory blockade, onset time and duration of motor blockade , total duration of analgesia and associated side effects. CONCLUSION : Dexmedetomidine as an adjuvant to ropivacaine in the supraclavicular brachial plexus block for upper limb surgeries , significantly shortens the onset time and prolongs the duration of sensory and motor blocks, with longer duration of post-operative analgesia , with associated significant sedation and a few manageable side effects like bradycardia and hypotension.

Evaluating upper limb function after stroke using the free-living accelerometer data

2020 ◽  
Vol 29 (11) ◽  
pp. 3249-3264 ◽  
Author(s):  
Lin Tang ◽  
Shane Halloran ◽  
Jian Qing Shi ◽  
Yu Guan ◽  
Chunzheng Cao ◽  
...  
Keyword(s):  
Upper Limb ◽  
Daily Living ◽  
Gaussian Mixture ◽  
Activity Level ◽  
Accelerometer Data ◽  
Free Living ◽  
Limb Function ◽  
Nonlinear Mixed Effects Model ◽  
Analysis Techniques ◽  
Upper Limb Function

Accelerometer devices are becoming efficient tools in clinical studies for automatically measuring the activities of daily living. Such data provides a time series describing activity level at every second and displays a subject’s activity pattern throughout a day. However, the analysis of such data is very challenging due to the large number of observations produced each second and the variability among subjects. The purpose of this study is to develop efficient statistical analysis techniques for predicting the recovery level of the upper limb function after stroke based on the free-living accelerometer data. We propose to use a Gaussian Mixture Model (GMM)-based method for clustering and extracting new features to capture the information contained in the raw data. A nonlinear mixed effects model with Gaussian Process prior for the random effects is developed as the predictive model for evaluating the recovery level of the upper limb function. Results of applying to the accelerometer data for patients after stroke are presented.

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