scholarly journals Wearable Sensor Based Stooped Posture Estimation in Simulated Parkinson’s Disease Gaits

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 223 ◽  
Author(s):  
Quoc Khanh Dang ◽  
Han Gil Seo ◽  
Duy Duong Pham ◽  
Youngjoon Chee
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dynamic Condition ◽  
Thoracolumbar Spine ◽  
Practical Method ◽  
Absolute Error ◽  
Wearable Sensor ◽  
Maximum Absolute Error ◽  
Optoelectronic System ◽  
Stooped Posture

Stooping is a posture which is described as an involuntary forward bending of the thoracolumbar spine. Conventionally, the stooped posture (SP) in Parkinson’s disease patients is measured in static or limited movement conditions using a radiological or optoelectronic system. In the dynamic condition with long movement distance, there was no effective method in preference to the empirical assessment from doctors. In this research, we proposed a practical method for estimating the SP with a high accuracy where accelerometers can be mounted on the neck or upper back as a wearable sensor. The experiments with simulated subjects showed a high correlation of 0.96 and 0.99 between the estimated SP angle and the reference angles for neck and back sensor position, respectively. The maximum absolute error (0.9 and 1.5 degrees) indicated that the system can be used, not only in clinical assessment as a measurement, but also in daily life as a corrector.

scholarly journals Quantitative assessment of gait parameters in people with Parkinson's disease in laboratory and clinical setting: Are the measures interchangeable?

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Massimiliano Pau ◽  
Federica Corona ◽  
Roberta Pili ◽  
Carlo Casula ◽  
Marco Guicciardi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Setting ◽  
Stride Length ◽  
Experimental Setting ◽  
Optoelectronic System ◽  
Double Support ◽  
Gait Parameters ◽  
Spatio Temporal ◽  
Wearable Accelerometers

This study aimed to investigate possible differences in spatio-temporal gait parameters of people with Parkinson’s Disease (pwPD) when they are tested either in laboratory using 3D Gait Analysis or in a clinical setting using wearable accelerometers. The main spatio-temporal gait parameters (speed, cadence, stride length, stance, swing and double support duration) of 31 pwPD were acquired: i) using a wearable accelerometer in a clinical setting while wearing shoes (ISS); ii) same as condition 1, but barefoot (ISB); iii) using an optoelectronic system (OES) undressed and barefoot. While no significant differences were found for cadence, stance, swing and double support duration, the experimental setting affected speed and stride length that decreased (by 17% and 12% respectively, P<0.005) when passing from the clinical (ISS) to the laboratory (OES) setting. These results suggest that gait assessment should be always performed in the same conditions to avoid errors, which may lead to inaccurate patient’s evaluations.

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.

Beneficial effect of levodopa therapy on stooped posture in Parkinson's disease

2015 ◽  
Vol 42 (3) ◽  
pp. 263-268 ◽  
Author(s):  
Felix Benninger ◽  
Alexander Khlebtovsky ◽  
Yaniv Roditi ◽  
Ofir Keret ◽  
Israel Steiner ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Beneficial Effect ◽  
Levodopa Therapy ◽  
Stooped Posture

scholarly journals A real-world study of wearable sensors in Parkinson’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jamie L. Adams ◽  
Karthik Dinesh ◽  
Christopher W. Snyder ◽  
Mulin Xiong ◽  
Christopher G. Tarolli ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Observational Study ◽  
Real World ◽  
Wearable Sensors ◽  
Clinic Visit ◽  
Accelerometer Data ◽  
Wearable Sensor ◽  
Steps Per Day ◽  
True Representation

AbstractMost wearable sensor studies in Parkinson’s disease have been conducted in the clinic and thus may not be a true representation of everyday symptoms and symptom variation. Our goal was to measure activity, gait, and tremor using wearable sensors inside and outside the clinic. In this observational study, we assessed motor features using wearable sensors developed by MC10, Inc. Participants wore five sensors, one on each limb and on the trunk, during an in-person clinic visit and for two days thereafter. Using the accelerometer data from the sensors, activity states (lying, sitting, standing, walking) were determined and steps per day were also computed by aggregating over 2 s walking intervals. For non-walking periods, tremor durations were identified that had a characteristic frequency between 3 and 10 Hz. We analyzed data from 17 individuals with Parkinson’s disease and 17 age-matched controls over an average 45.4 h of sensor wear. Individuals with Parkinson’s walked significantly less (median [inter-quartile range]: 4980 [2835–7163] steps/day) than controls (7367 [5106–8928] steps/day; P = 0.04). Tremor was present for 1.6 [0.4–5.9] hours (median [range]) per day in most-affected hands (MDS-UPDRS 3.17a or 3.17b = 1–4) of individuals with Parkinson’s, which was significantly higher than the 0.5 [0.3–2.3] hours per day in less-affected hands (MDS-UPDRS 3.17a or 3.17b = 0). These results, which require replication in larger cohorts, advance our understanding of the manifestations of Parkinson’s in real-world settings.

Tossing and Turning in Bed: A Wearable Sensor Documents Abnormal Nocturnal Movements in Parkinson's Disease

2019 ◽  
Author(s):  
Anat Mirelman ◽  
Inbar Hillel ◽  
Lynn Rochester ◽  
Silvia Del Din ◽  
Bastiaan R. Bloem ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Wearable Sensor

scholarly journals Parkinson’s Disease Rating Scale Using Synchronization Analysis of Gait Dynamics

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Naeimehossadat Asmarian ◽  
Ahmad Ruzitalab ◽  
Gholamhossien Erjaee ◽  
Mohammad Hadi Farahi ◽  
Seyyed Mojtaba Asmarian
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scale ◽  
Massachusetts General Hospital ◽  
Rank Correlation ◽  
Absolute Error ◽  
Time Interval ◽  
Gait Dynamics ◽  
Data Phase ◽  
Yahr Scale

Analysis of gait dynamics is a noninvasive and totally painless test, and it can be an ideal method for the diagnosis of neurodegenerative diseases. In this study, based on the strength of synchronization between dynamics of strides, we have suggested a rating scale method for Parkinson’s disease (PD). Methods. The sample included 15 persons with PD (age: 66.8 ± 10.9 years) and 16 healthy persons (age: 39.3 ± 18.5   years) which were recruited from the Neurology Outpatient Clinic at Massachusetts General Hospital and were instructed to walk a 77 m long, straight hallway. The time interval of strides and subphases of strides were measured. Using the Hilbert transformation method, we obtained the data phase and used mean absolute error (MAE) to calculate the synchronization strength of the data phase. Results. In order to check the accuracy of our method, we measured the correlation between our numerical results (MAE) and values of the Hoehn-Yahr scale. Spearman’s rank correlation coefficients ( r ) and the P values were calculated. MAE of left and right stride intervals (LRSI) significantly correlates with the Hoehn-Yahr scale for the subjects with PD (with r = 0.60 and P = 0.025 < 0.05 ). Conclusion. We have revealed that the synchronization weakness of LRSI shows the severity of PD. This method seems to be well suited as a rating scale for people with PD.

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