Prediction of ground reaction forces for Parkinson's disease patients using a kinect-driven musculoskeletal gait analysis model

2017 ◽  
Vol 50 ◽  
pp. 75-82 ◽  
Author(s):  
Moataz Eltoukhy ◽  
Christopher Kuenze ◽  
Michael S. Andersen ◽  
Jeonghoon Oh ◽  
Joseph Signorile
2011 ◽  
Vol 106 (2) ◽  
pp. 915-924 ◽  
Author(s):  
Mark W. Rogers ◽  
Robert Kennedy ◽  
Sonia Palmer ◽  
Monika Pawar ◽  
Maggie Reising ◽  
...  

People with Parkinson's disease (PD) frequently have difficulties with generating anticipatory postural adjustments (APAs) for forward propulsion and lateral weight transfer when initiating gait. This impairment has been attributed to deficits in motor planning and preparation. This study examined the preparation of APAs prior to an imperative cue to initiate forward stepping. A startling acoustic stimulus (SAS) was used to probe the state of preparation of the APA in eight PD (off medication) and seven matched control subjects. Subjects performed visually cued trials involving a pre-cue light instructing them to prepare to step, followed 3.5 s later by a go-cue light to rapidly initiate stepping. In random trials, a SAS (124 dB) was presented at −1,500, −1,000, −500, −250, −100, or 0 ms before the go-cue. Subjects also performed self-initiated steps. Ground reaction forces (GRFs), center of pressure (CoP) changes, and electromyographic (EMG) signals were recorded. The SAS triggered APAs in 94 ± 11% (PD) and 96 ± 8% (control) of trials at latencies 89 ± 4 ms (PD) and 97 ± 3 ms (control) earlier than Control trials. The temporal profile of APA preparation was similar between groups. However, peak EMG, GRF, and mediolateral CoP amplitudes were reduced in PD. SAS-evoked APAs at 0 ms matched Control trial APAs and were enhanced compared with self-initiated stepping. These results demonstrate that people with mild to moderate PD can plan and prepare the appropriate APA sequence prior to the expected cue to initiate gait; however, the prepared APAs are underscaled in magnitude.


Author(s):  
Pei Huang ◽  
Yuan-Yuan Li ◽  
Jung E. Park ◽  
Ping Huang ◽  
Qin Xiao ◽  
...  

ABSTRACT: We investigated the effects of botulinum toxin on gait in Parkinson’s disease (PD) patients with foot dystonia. Six patients underwent onabotulinum toxin A injection and were assessed by Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), visual analog scale (VAS) of pain, Timed Up and Go (TUG), Berg Balance Test (BBT), and 3D gait analysis at baseline, 1 month, and 3 months. BFMDRS (p = 0.002), VAS (p = 0.024), TUG (p = 0.028), and BBT (p = 0.034) were improved. Foot pressures at Toe 1 (p = 0.028) and Midfoot (p = 0.018) were reduced, indicating botulinum toxin’s effects in alleviating the dystonia severity and pain and improving foot pressures during walking in PD.


2019 ◽  
Vol 5 (1) ◽  
pp. 9-12
Author(s):  
Jyothsna Kondragunta ◽  
Christian Wiede ◽  
Gangolf Hirtz

AbstractBetter handling of neurological or neurodegenerative disorders such as Parkinson’s Disease (PD) is only possible with an early identification of relevant symptoms. Although the entire disease can’t be treated but the effects of the disease can be delayed with proper care and treatment. Due to this fact, early identification of symptoms for the PD plays a key role. Recent studies state that gait abnormalities are clearly evident while performing dual cognitive tasks by people suffering with PD. Researches also proved that the early identification of the abnormal gaits leads to the identification of PD in advance. Novel technologies provide many options for the identification and analysis of human gait. These technologies can be broadly classified as wearable and non-wearable technologies. As PD is more prominent in elderly people, wearable sensors may hinder the natural persons movement and is considered out of scope of this paper. Non-wearable technologies especially Image Processing (IP) approaches captures data of the person’s gait through optic sensors Existing IP approaches which perform gait analysis is restricted with the parameters such as angle of view, background and occlusions due to objects or due to own body movements. Till date there exists no researcher in terms of analyzing gait through 3D pose estimation. As deep leaning has proven efficient in 2D pose estimation, we propose an 3D pose estimation along with proper dataset. This paper outlines the advantages and disadvantages of the state-of-the-art methods in application of gait analysis for early PD identification. Furthermore, the importance of extracting the gait parameters from 3D pose estimation using deep learning is outlined.


1998 ◽  
Vol 13 (6) ◽  
pp. 900-906 ◽  
Author(s):  
John D. O'Sullivan ◽  
Catherine M. Said ◽  
Louise C. Dillon ◽  
Marion Hoffman ◽  
Andrew J. Hughes

2015 ◽  
Vol 584 ◽  
pp. 184-189 ◽  
Author(s):  
Ming Zhou ◽  
Wangming Zhang ◽  
Jingyu Chang ◽  
Jun Wang ◽  
Weixin Zheng ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Micaela Porta ◽  
Giuseppina Pilloni ◽  
Roberta Pili ◽  
Carlo Casula ◽  
Mauro Murgia ◽  
...  

Background. Although physical activity (PA) is known to be beneficial in improving motor symptoms of people with Parkinson’s disease (pwPD), little is known about the relationship between gait patterns and features of PA performed during daily life. Objective. To verify the existence of possible relationships between spatiotemporal and kinematic parameters of gait and amount/intensity of PA, both instrumentally assessed. Methods. Eighteen individuals affected by PD (10F and 8M, age 68.0 ± 10.8 years, 1.5 ≤ Hoehn and Yahr (H&Y) < 3) were required to wear a triaxial accelerometer 24 h/day for 3 consecutive months. They also underwent a 3D computerized gait analysis at the beginning and end of the PA assessment period. The number of daily steps and PA intensity were calculated on the whole day, and the period from 6:00 to 24:00 was grouped into 3 time slots, using 3 different cut-point sets previously validated in the case of both pwPD and healthy older adults. 3D gait analysis provided spatiotemporal and kinematic parameters of gait, including summary indexes of quality (Gait Profile Score (GPS) and Gait Variable Score (GVS)). Results. The analysis of hourly trends of PA revealed the existence of two peaks located in the morning (approximately at 10) and in the early evening (between 18 and 19). However, during the morning time slot (06:00–12:00), pwPD performed significantly higher amounts of steps (4313 vs. 3437 in the 12:00–18:00 time slot, p<0.001, and vs. 2889 in the 18:00–24:00 time slot, p=0.021) and of moderate-to-vigorous PA (43.2% vs. 36.3% in the 12:00–18:00 time slot, p=0.002, and vs. 31.4% in the 18:00–24:00 time slot, p=0.049). The correlation analysis shows that several PA intensity parameters are significantly associated with swing-phase duration (rho = −0.675 for sedentary intensity, rho = 0.717 for moderate-to-vigorous intensity, p<0.001), cadence (rho = 0.509 for sedentary intensity, rho = −0.575 for moderate-to-vigorous intensity, p<0.05), and overall gait pattern quality as expressed by GPS (rho = −0.498 to −0.606 for moderate intensity, p<0.05) and GVS of knee flexion-extension (rho = −0.536 for moderate intensity, p<0.05). Conclusions. Long-term monitoring of PA integrated by the quantitative assessment of spatiotemporal and kinematic parameters of gait may represent a useful tool in supporting a better-targeted prescription of PA and rehabilitative treatments in pwPD.


2020 ◽  
Vol 79 ◽  
pp. 86-91
Author(s):  
Sergio Clavijo-Buendía ◽  
Francisco Molina-Rueda ◽  
Patricia Martín-Casas ◽  
Paulina Ortega-Bastidas ◽  
Esther Monge-Pereira ◽  
...  

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