Gait analysis and clinical correlations in early Parkinson�s disease

Pistacchi, Michele

doi:10.11138/fneur/2017.32.1.028

Cited by 190 publications

(133 citation statements)

References 32 publications

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“…Another aspect might be related to the control group -though we were assured by the family doctor that helped with recruiting the control group that the subjects were currently healthy and free of possible limitations, they still had some health restrictions, possibly somewhat influencing the result. The step walk ratio in the present study was 6.0 mm/(step/min) -this result stays below walk ratio considered to be constant for healthy adults (6.5 mm/(step/min) [19].…”

Section: Discussioncontrasting

confidence: 75%

“…Disturbances in spatiotemporal parameters of gait are well documented in patients with PD [3,7,12,19,21]. Though there are numerous data that also gait kinematics and kinetics are altered by PD [10,25], it was not of interest to analyse these parameters in the present study.…”

Section: Discussionmentioning

confidence: 99%

“…In agreement with previous findings [12,14], the cadence was similar in both measurements in PD patients and the controls. Some studies [17,19] have suggested that patients with PD have higher cadence to compensate the reduced stride length. Nieuwboer et al [17] reported an exponential increase of cadence with a decreasing stride length during freezing.…”

Section: Discussionmentioning

confidence: 99%

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Gait parameters of individuals with Parkinson disease decline during one-year period

Medijainen

Lukmann

Taba

2020

AKUT

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Parkinson’s disease (PD) is a neurodegenerative disease, influencing mainly elderly. The key motor factor affecting the level of participation in activities of daily living is the gait function, which is known to be progressively impaired in PD. However, gait characteristics also worsen due to normal aging. The main aim of this study was to investigate whether gait parameters decline in individuals with PD in an interval of one year compared to healthy elderly. Selected gait characteristics were recorded using 3-D optoelectronic movement analysis system ELITE in 13 patients with mild-to-moderate PD and 13 age- and gender-matched controls. Hoehn and Yahr Scale and Unified Parkinson Disease Rating Scale were used for clinical assessment. It was found that PD patients walk with significantly shorter steps and stride and reduced gait speed. In one year, the stride length initiated with right foot and stride walk ratio further decrease in PD patients. On re-evaluation the percentages of stance, swing and double support phase differed significantly between groups. In second measurement, control subjects walked with reduced step width. It was concluded that gait speed and stride length decline in patients with PD in a period of one year, whereas no indication of deterioration of gait function is evident in healthy controls.

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Section: Discussioncontrasting

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Gait parameters of individuals with Parkinson disease decline during one-year period

Medijainen

Lukmann

Taba

2020

AKUT

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“…Gait analysis showed 2-month-old A30P mice are pre-symptomatic (psA30P mice) Gait analysis has been used to show onset of obvious PD manifestations in mice 40 . We analyzed ten gait parameters of A30P and wild type (WT) mice using the CatWalk XT system.…”

Section: Resultsmentioning

confidence: 99%

Functional and molecular early enteric biomarkers for Parkinson’s disease in mice and men

Gries

Christmann

Schulte

et al. 2020

Preprint

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Parkinson's disease (PD) usually has a late clinical onset. The lack of early biomarkers for the disease represents a major challenge for developing timely treatment interventions. Here, we use an -synuclein-overexpressing transgenic (Th-1-SNCA-A30P) mouse model of PD to identify appropriate candidate markers in the gut for early stages of PD before hallmark symptoms begin to manifest. A30P mice did not show alterations in gait parameters at 2 months of age, and these mice were therefore defined as pre-symptomatic A30P mice (psA30P). We discovered early functional motility changes in the gut and early molecular dysregulations in the myenteric plexus of psA30P mice by comparative protein and miRNA profiling and cell culture experiments. We found that the proteins neurofilament light chain, vesicle-associated membrane protein 2 and calbindin 2, together with the miRNAs that regulate them, are potential biomarkers of early PD that may facilitate timely treatment and/or prevention of PD in men.

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“…Despite the significant interest in parkinsonian gait analysis, there is no objective tool to assist physicians for gait evaluation. Since changes in the gait are among the first symptoms of this disease (Pistacchi et al, 2017), a powerful gait classifier would be helpful for physicians. In this clinical context, the objective of our research work is to develop an intelligent tool to detect Parkinson's disease symptoms and predict the Parkinson severity rate (based on the UPDRS) from gait data.…”

Section: Introductionmentioning

confidence: 99%

Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait

Maâchi

Bilodeau

Bouachir

2020

Expert Systems with Applications

175

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Diagnosing Parkinson's disease is a complex task that requires the evaluation of several motor and non-motor symptoms. During diagnosis, gait abnormalities are among the important symptoms that physicians should consider. However, gait evaluation is challenging and relies on the expertise and subjectivity of clinicians. In this context, the use of an intelligent gait analysis algorithm may assist physicians in order to facilitate the diagnosis process. This paper proposes a novel intelligent Parkinson detection system based on deep learning techniques to analyze gait information. We used 1D convolutional neural network (1D-Convnet) to build a Deep Neural Network (DNN) classifier. The proposed model processes 18 1D-signals coming from foot sensors measuring the vertical ground reaction force (VGRF). The first part of the network consists of 18 parallel 1D-Convnet corresponding to system inputs. The second part is a fully connected network that connects the concatenated outputs of the 1D-Convnets to obtain a final classification. the severity of the disease with the Unified Parkinson's Disease Rating Scale (UPDRS). Our experiments demonstrate the high efficiency of the proposed method in the detection of Parkinson disease based on gait data. The proposed algorithm achieved an accuracy of 98.7%. To our knowledge, this is the state-of-the-start performance in Parkinson's gait recognition. Furthermore, we achieved an accuracy of 85.3% in Parkinson's severity prediction.To the best of our knowledge, this is the first algorithm to perform a severity prediction based on the UPDRS.These results show that the model is able to learn intrinsic characteristics from gait data and to generalize to unseen subjects, which could be helpful in a clinical diagnosis.

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Gait analysis and clinical correlations in early Parkinson�s disease

Cited by 190 publications

References 32 publications

Gait parameters of individuals with Parkinson disease decline during one-year period

Gait parameters of individuals with Parkinson disease decline during one-year period

Functional and molecular early enteric biomarkers for Parkinson’s disease in mice and men

Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait

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