scholarly journals SELF STABILISING UTENSIL FOR PATIENTS WITH IMPAIRED MOTOR SKILLS

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Nikita Jain ◽  
Rishika I.S ◽  
Kusuma K.B ◽  
Dr. Manisha Shivaram Joshi
Keyword(s):  
Parkinson’S Disease ◽  
Motor Skills ◽  
Inertial Measurement Unit ◽  
Daily Activities ◽  
Stepper Motor ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Non Invasive ◽  
Invasive Device ◽  
The Given

- Nowadays, there is a substantial increase in the number of people getting affected by Parkinson's Disease. The degradations of motor skills severely affect the daily activities of patients such as eating, writing, dressing, etc. This project basically proposes a non-invasive device that helps the patient to eat and perform day to day chores independently using the given attachments. This device consists of Arduino which directs the two stepper motor to cancel the tremors detected by the Inertial Measurement Unit (MPU6050) containing 3 axis gyroscope and 3 axis accelerometer which senses these tremors.

scholarly journals Integrated GNSS/IMU-Gyrocompass with Rotating IMU. Development and Test Results

2020 ◽  
Vol 12 (22) ◽  
pp. 3736
Author(s):  
Gennadiy Emel’yantsev ◽  
Oleg Stepanov ◽  
Aleksey Stepanov ◽  
Boris Blazhnov ◽  
Elena Dranitsyna ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Fiber Optic ◽  
Measurement Unit ◽  
Prototype Model ◽  
Navigation Satellite ◽  
Test Results ◽  
Rotating Platform ◽  
Inertial Measurement ◽  
Urban Conditions ◽  
The Given

The paper presents the developed integrated GNSS/IMU gyrocompass which, unlike the existing systems, contains a single-axis rotating platform with two antennas installed on it and an inertial measurement unit with tactical grade fiber-optic gyros. It is shown that the proposed design provides attitude solution by observing the signals of only one navigation satellite. The structure of the integrated GNSS/IMU gyrocompass, its specific features and prototype model used in the tests are described. The given test results in urban conditions confirmed heading determination accurate to ±1.5° (3σ).

scholarly journals Deep learning for freezing of gait detection in Parkinson’s disease patients in their homes using a waist-worn inertial measurement unit

2018 ◽  
Vol 139 ◽  
pp. 119-131 ◽  
Author(s):  
Julià Camps ◽  
Albert Samà ◽  
Mario Martín ◽  
Daniel Rodríguez-Martín ◽  
Carlos Pérez-López ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Inertial Measurement Unit ◽  
Freezing Of Gait ◽  
Measurement Unit ◽  
Inertial Measurement

scholarly journals A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients

Sensors ◽  
2017 ◽  
Vol 17 (4) ◽  
pp. 827 ◽  
Author(s):  
Daniel Rodríguez-Martín ◽  
Carlos Pérez-López ◽  
Albert Samà ◽  
Andreu Català ◽  
Joan Moreno Arostegui ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Wearable device intended for detection of fog episodes in Parkinson´s disease

2019 ◽  
Vol 13 (1) ◽  
pp. 10-16
Author(s):  
Laura Carolina Rozo Hoyos ◽  
Juan Pablo Pulgarín González ◽  
Paula Andrea Morales Fandiño ◽  
Jonathan Gallego Londoño
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inertial Measurement Unit ◽  
Freezing Of Gait ◽  
Wearable Device ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Normal Gait ◽  
Fog Prediction ◽  
Advanced Stages

The episodes of Freezing of Gait (FOG) are a recurring symptom in people suffering from advanced stages of Parkinson's disease (PD). These are severe occurrences because they may cause falls to the patients, generating further traumas and concussions. In order to solve this yet ineffectively treated issue, this article describes the research that developed a device capable of predicting freezing episodes. On this project a wearable device was developed, which was able to predict freezing episodes based on the calculation of a freezing index (FI) determined by the signals obtained from an inertial measurement unit (IMU). This device was tested in three Patients and signals corresponding to normal gait and simulated Parkinson gait were taken. The results showed that FI obtained from Parkinson gait were much higher than those from a normal gait, validating this parameter as a key aspect in FOG prediction.      

scholarly journals A Multi-Sensor Cane Can Detect Changes in Gait Caused by Simulated Gait Abnormalities and Walking Terrains

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 631 ◽  
Author(s):  
Satinder Gill ◽  
Nitin Seth ◽  
Erik Scheme
Keyword(s):  
Chronic Diseases ◽  
Inertial Measurement Unit ◽  
Assistive Devices ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Impaired Vision ◽  
Inertial Measurement ◽  
Non Invasive ◽  
Gait Abnormalities ◽  
Healthy Participants

Due to the increasing rates of chronic diseases and an aging population, the use of assistive devices for ambulation is expected to grow rapidly over the next several years. Instrumenting these devices has been proposed as a non-invasive way to proactively monitor changes in gait due to the presence of pain or a condition in outdoor and indoor environments. In this paper, we evaluated the effectiveness of a multi-sensor cane in detecting changes in gait due to the presence of simulated gait abnormalities, walking terrains, impaired vision, and incorrect cane lengths. The effectiveness of the instrumented cane was compared with the results obtained directly from a shank-mounted inertial measurement unit. Results from 30 healthy participants obtained while simulating gait abnormalities and walking over different terrains demonstrated the ability of the cane to reliably and effectively discriminate among these walking conditions. Moreover, the results obtained while walking with impaired vision and incorrect cane lengths indicate the ability of cane to detect changes in gait during these scenarios as well.

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