A Wheelchair Simulator Using Limited-Motion Patterns and Vection-Inducing Movies

2019 ◽  
Author(s):  
Akihiro Miyata ◽  
Kousuke Motooka ◽  
Kenro Go
Keyword(s):  
Motion Patterns ◽  
Limited Motion

scholarly journals Tongue Motion Patterns in Post-Glossectomy and Typical Speakers: A Principal Components Analysis

2014 ◽  
Vol 57 (3) ◽  
pp. 707-717 ◽  
Author(s):  
Maureen Stone ◽  
Julie M. Langguth ◽  
Jonghye Woo ◽  
Hegang Chen ◽  
Jerry L. Prince
Keyword(s):  
Principal Components ◽  
Magnetic Resonance Images ◽  
Velocity Fields ◽  
Motion Patterns ◽  
Adaptive Motion ◽  
The Subject ◽  
Components Analysis ◽  
Left Middle ◽  
Limited Motion ◽  
Tongue Motion

Purpose In this study, the authors examined changes in tongue motion caused by glossectomy surgery. A speech task that involved subtle changes in tongue-tip positioning (the motion from /i/ to /s/) was measured. The hypothesis was that patients would have limited motion on the tumor (resected) side and would compensate with greater motion on the nontumor side in order to elevate the tongue tip and blade for /s/. Method Velocity fields were extracted from tagged magnetic resonance images in the left, middle, and right tongue of 3 patients and 10 controls. Principal components (PCs) analysis quantified motion differences and distinguished between the subject groups. Results PCs 1 and 2 represented variance in (a) size and independence of the tongue tip, and (b) direction of motion of the tip, body, or both. Patients and controls were correctly separated by a small number of PCs. Conclusions Motion of the tumor slice was different between patients and controls, but the nontumor side of the patients' tongues did not show excessive or adaptive motion. Both groups contained apical and laminal /s/ users, and 1 patient created apical /s/ in a highly unusual manner.

Questions and Answers

2000 ◽  
Vol 5 (2) ◽  
pp. 3-3
Author(s):  
Christopher R. Brigham ◽  
James B. Talmage
Keyword(s):  
Nervous System ◽  
Peripheral Nervous System ◽  
Spinal Nerve ◽  
Sensory Loss ◽  
Residual Symptoms ◽  
Additional Information ◽  
Questions And Answers ◽  
Motor Nerves ◽  
Symptoms And Signs ◽  
Limited Motion

Abstract Lesions of the peripheral nervous system (PNS), whether due to injury or illness, commonly result in residual symptoms and signs and, hence, permanent impairment. The AMA Guides to the Evaluation of Permanent Impairment (AMA Guides) describes procedures for rating upper extremity neural deficits in Chapter 3, The Musculoskeletal System, section 3.1k; Chapter 4, The Nervous System, section 4.4 provides additional information and an example. The AMA Guides also divides PNS deficits into sensory and motor and includes pain within the former. The impairment estimates take into account typical manifestations such as limited motion, atrophy, and reflex, trophic, and vasomotor deficits. Lesions of the peripheral nervous system may result in diminished sensation (anesthesia or hypesthesia), abnormal sensation (dysesthesia or paresthesia), or increased sensation (hyperesthesia). Lesions of motor nerves can result in weakness or paralysis of the muscles innervated. Spinal nerve deficits are identified by sensory loss or pain in the dermatome or weakness in the myotome supplied. The steps in estimating brachial plexus impairment are similar to those for spinal and peripheral nerves. Evaluators should take care not to rate the same impairment twice, eg, rating weakness resulting from a peripheral nerve injury and the joss of joint motion due to that weakness.

Tongue and Lip Motion Patterns in Alaryngeal Speech

2020 ◽  
Author(s):  
Kristin J. Teplansky ◽  
Alan Wisler ◽  
Beiming Cao ◽  
Wendy Liang ◽  
Chad W. Whited ◽  
...  
Keyword(s):  
Motion Patterns ◽  
Alaryngeal Speech

scholarly journals Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses—A Machine Learning Approach

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 798
Author(s):  
Hamed Darbandi ◽  
Filipe Serra Bragança ◽  
Berend Jan van der Zwaag ◽  
John Voskamp ◽  
Annik Imogen Gmel ◽  
...  
Keyword(s):  
Machine Learning ◽  
The Body ◽  
Biomechanical Analysis ◽  
Estimation Accuracy ◽  
Speed Estimation ◽  
Motion Patterns ◽  
Positioning Systems ◽  
Machine Learning Approach ◽  
Global Positioning ◽  
Measurement Units

Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU signals integration. In an attempt to overcome these issues, we have investigated the possibility of estimating the horse speed by developing machine learning (ML) models using the signals from seven body-mounted IMUs. Since motion patterns extracted from IMU signals are different between breeds and gaits, we trained the models based on data from 40 Icelandic and Franches-Montagnes horses during walk, trot, tölt, pace, and canter. In addition, we studied the estimation accuracy between IMU locations on the body (sacrum, withers, head, and limbs). The models were evaluated per gait and were compared between ML algorithms and IMU location. The model yielded the highest estimation accuracy of speed (RMSE = 0.25 m/s) within equine and most of human speed estimation literature. In conclusion, highly accurate horse speed estimation models, independent of IMU(s) location on-body and gait, were developed using ML.

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