Arm swing asymmetry in Parkinson's disease measured with ultrasound based motion analysis during treadmill gait

2012 ◽  
Vol 35 (1) ◽  
pp. 116-120 ◽  
Author(s):  
J. Roggendorf ◽  
S. Chen ◽  
S. Baudrexel ◽  
S. van de Loo ◽  
C. Seifried ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motion Analysis ◽  
Arm Swing

scholarly journals Clinical Differentiation of Essential Tremor and Parkinson's Disease

2013 ◽  
Vol 6 ◽  
pp. CCRep.S11903 ◽  
Author(s):  
Robert Fekete ◽  
Jin Li
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Essential Tremor ◽  
Single Photon ◽  
Photon Emission ◽  
Emission Computed Tomography ◽  
Postural Tremor ◽  
Arm Swing ◽  
Rest Tremor ◽  
Dopaminergic Terminal

We present clinical features and tremor characterization in a patient with Parkinson's disease (PD) as well as in two cases of essential tremor (ET) with some parkinsonian features but no evidence of dopaminergic terminal loss on 123I-FP-CIT Single Photon Emission Computed Tomography (SPECT). Relatively slow frequency rest tremor and bilateral upper extremity bradykinesia without decrementing amplitude were observed in the ET cases, with unilaterally decreased arm swing in case 3. Alternating rest tremor and re-emergent tremor with 13 second latency was confirmed in the PD case. Re-emergent tremor had alternating characteristics, which to our knowledge has not been previously reported. The ET cases had synchronous postural tremor. Alternating re-emergent tremor in PD provides further evidence for re-emergent tremor as an analogue of rest tremor in PD. Two cases of ET with synchronous postural tremor and one to two year history of parkinsonian features had no evidence of dopaminergic terminal loss up to 40 years after the initial onset of ET. Tremor synchronicity characterization can assist in differential diagnosis between the two disorders.

scholarly journals Quantification of Arm Swing during Walking in Healthy Adults and Parkinson’s Disease Patients: Wearable Sensor-Based Algorithm Development and Validation

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5963 ◽  
Author(s):  
Elke Warmerdam ◽  
Robbin Romijnders ◽  
Julius Welzel ◽  
Clint Hansen ◽  
Gerhard Schmidt ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Angular Velocity ◽  
Wearable Sensors ◽  
Healthy Adults ◽  
Wearable Sensor ◽  
Arm Swing ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Development And Validation

Neurological pathologies can alter the swinging movement of the arms during walking. The quantification of arm swings has therefore a high clinical relevance. This study developed and validated a wearable sensor-based arm swing algorithm for healthy adults and patients with Parkinson’s disease (PwP). Arm swings of 15 healthy adults and 13 PwP were evaluated (i) with wearable sensors on each wrist while walking on a treadmill, and (ii) with reflective markers for optical motion capture fixed on top of the respective sensor for validation purposes. The gyroscope data from the wearable sensors were used to calculate several arm swing parameters, including amplitude and peak angular velocity. Arm swing amplitude and peak angular velocity were extracted with systematic errors ranging from 0.1 to 0.5° and from −0.3 to 0.3°/s, respectively. These extracted parameters were significantly different between healthy adults and PwP as expected based on the literature. An accurate algorithm was developed that can be used in both clinical and daily-living situations. This algorithm provides the basis for the use of wearable sensor-extracted arm swing parameters in healthy adults and patients with movement disorders such as Parkinson’s disease.

scholarly journals The power of musification: sensor‐based music feedback improves arm swing in Parkinson's disease

2021 ◽  
Author(s):  
Stefan Mainka ◽  
Arno Schroll ◽  
Elke Warmerdam ◽  
Florin Gandor ◽  
Walter Maetzler ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Arm Swing

scholarly journals Analysis and Classification of Motor Dysfunctions in Arm Swing in Parkinson’s Disease

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1471 ◽  
Author(s):  
Tobias Steinmetzer ◽  
Michele Maasch ◽  
Ingrid Bönninger ◽  
Carlos M. Travieso
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Wavelet Transformation ◽  
Inertial Sensors ◽  
Arm Movement ◽  
Objective Evaluation ◽  
Timed Up And Go ◽  
Arm Swing ◽  
Age Related ◽  
Wearable Inertial Sensors

Due to increasing life expectancy, the number of age-related diseases with motor dysfunctions (MD) such as Parkinson’s disease (PD) is also increasing. The assessment of MD is visual and therefore subjective. For this reason, many researchers are working on an objective evaluation. Most of the research on gait analysis deals with the analysis of leg movement. The analysis of arm movement is also important for the assessment of gait disorders. This work deals with the analysis of the arm swing by using wearable inertial sensors. A total of 250 records of 39 different subjects were used for this task. Fifteen subjects of this group had motor dysfunctions (MD). The subjects had to perform the standardized Timed Up and Go (TUG) test to ensure that the recordings were comparable. The data were classified by using the wavelet transformation, a convolutional neural network (CNN), and weight voting. During the classification, single signals, as well as signal combinations were observed. We were able to detect MD with an accuracy of 93.4% by using the wavelet transformation and a three-layer CNN architecture.

A46 A rising motion analysis of Parkinson's disease patient in a chair

2011 ◽  
Vol 2011 (0) ◽  
pp. 235-240
Author(s):  
Noriyuki OHBAYASHI ◽  
Shigeru AOMURA ◽  
Hiromichi NAKADATE ◽  
Osamu NITTA
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motion Analysis ◽  
Disease Patient
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