Personalized rehabilitation assessment of locomotor functions in Parkinson disease using three-dimensional video analysis of motions

Прокопенко, С. В.; Mozheiko, E.Yu.; Abroskina, M V; Ondar, V. S.; Ismailova, S. B.; Subocheva, S A; Khomchenkova, Alexandra A.; Gurevich, V.A.; Zubritskaya, E. M.; Малков, А. Б.; Kondratyev, S. N.

doi:10.30629/2658-7947-2021-26-1-23-33

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…where y(d i , C j ) is the classification value of the text pair category in the training set, and its value range is {0, 1} [14].…”

Section: Feature Extraction Pattern Recognitionmentioning

confidence: 99%

Design and Implementation of Personalized Push Service Based on Feature Extraction and Pattern Recognition

Zhang¹

2022

Computational Intelligence and Neuroscience

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Personalized push service is one of the more popular research and application fields, which has received more and more attention. Its application prospects are also more and more extensive. This research mainly designs and implements personalized push services through feature extraction and pattern recognition. In this study, the Chinese texts of user-visited pages are classified according to keywords, so as to obtain the user’s interest characteristic data. Then, according to the frequency of each feature category, the weight of the user’s interest feature is calculated, and the user’s interest field is predicted and identified. After that, resources that match the user’s interest field are pushed to it. In order to verify the effectiveness of the improved model, this study carried out experiments and comparisons on the precision rate, recall rate, and comprehensive classification rate of the original model and the improved model on the implemented personalized push service system. In the research, the error between the interest results under each interest topic in the test set and the results obtained by the statistical analysis of the training set is within a reasonable range, the maximum of which is about 5%. The accuracy of interest degree prediction in different scenarios can reach more than 90%, which directly confirms the good applicability and effectiveness of the analysis and calculation method and the constructed model for user interest in this study. The personalized push service framework proposed in this study has good application value in the field of time-sensitive information services.

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“…where y(d i , C j ) is the classification value of the text pair category in the training set, and its value range is {0, 1} [14].…”

Section: Feature Extraction Pattern Recognitionmentioning

confidence: 99%

Design and Implementation of Personalized Push Service Based on Feature Extraction and Pattern Recognition

Zhang¹

2022

Computational Intelligence and Neuroscience

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The effect of the Pisa syndrome on balance and gait in Parkinson’s disease: a comparative study

Nazarova,

Nalobina

2024

Bulletin of Rehabilitation Medicine

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INTRODUCTION. Pisa syndrome is a postural deformity that can lead to impaired posture control and balance in patients with Parkinson’s disease (PD), which increases the risk of injury and reduces the quality of life. AIM. To study the effect of the Pisa syndrome on postural control, balance and gait of patients with Parkinson’s disease. HYPOTHESIS. It is assumed that patients with PD with the Pisa syndrome will have specific features of postural control and balance, which must be taken into account when developing rehabilitation technologies for correcting postural disorders. MATERIALS AND METHODS. As part of the comparative study, 30 people of both sexes were examined, all study participants received levodopa drugs in an individual dosage selected by a neurologist-parkinsonologist. The subjects were divided into 2 groups of 15 people each according to the principle of the presence of the Pisa syndrome and its absence. Criteria for inclusion in the groups: voluntary informed consent of persons with PD for the study; age from 45–80 years, stage 2–4 of Hoehn-Yahr Parkinson’s disease, absence of other diseases and gross cognitive impairment. The diagnosis was carried out using the COBS Physiomed stabilometry system and the EQ-5D-3L questionnaire, a diary of falls and a dynamic gait index (DGI). The reliability of the differences was determined by the Mann-Whitney U-test. Data processing was carried out using the Statistica 10 program. RESULTS. Significant differences were revealed in the parameter of the coordination index of the Standing Balance test for the right leg and on the EQ-5D-3L scale at a significance level of p 0.05, in the group of people with PD without the Pisa syndrome, the quality of life was significantly higher, the number of falls was significantly higher in the group of people suffering from PD with the Pisa syndrome towers. DISCUSSION. Walking with a change of direction and multitasking is the most significant problem for people with PD with the Pisa syndrome, the differences between the groups are significant at a significance level of p 0.01. CONCLUSION. Patients with PD and Pisa syndrome have altered gait associated with body tilt forward, instability and decreased balance control.

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Personalized rehabilitation assessment of locomotor functions in Parkinson disease using three-dimensional video analysis of motions

Cited by 2 publications

References 19 publications

Design and Implementation of Personalized Push Service Based on Feature Extraction and Pattern Recognition

Design and Implementation of Personalized Push Service Based on Feature Extraction and Pattern Recognition

The effect of the Pisa syndrome on balance and gait in Parkinson’s disease: a comparative study

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