Xiying Li¹, Alyx Taylor², Jinming Li³, Ting Wang³, Jing Kuang³, Zhihao Zhang³, Xiaolei Liu⁴, Tingting Liu⁴, Xia Qin⁵, Shenghua Lu^6,7,*, Liye Zou³

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 855-867, 2022, DOI:10.32604/ijmhp.2022.021508

Abstract Objective: This study explored the effects of Health Qigong exercise on depression and anxiety in patients with Parkinson’s disease (PD). Methods: A total of 42 volunteers who met the inclusion criteria were recruited and randomly allocated into the experimental group and the control group. The experimental group carried out 60-minute sessions of Health Qigong exercise five times a week for 12 weeks while the control group did not perform any regular physical exercise. Data on cognitive impairment, psychomotor retardation, somatic anxiety, weight loss and sleep disorders, the sum score of the 17-item Hamilton Depression Rating Scale (HDRS-17), state anxiety, trait… More >

Rita Yi Man Li¹, Lingxi Song², Bo Li^2,3, M. James C. Crabbe^4,5,6, Xiao-Guang Yue^7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2247-2282, 2023, DOI:10.32604/cmes.2022.020930

Abstract The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword “carpark” in Google Scholar, the largest electronic academic database that covers Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced… More > Graphic Abstract

C. Santhosh Kumar¹, K. Vishnu Kumar^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2893-2907, 2023, DOI:10.32604/iasc.2023.029669

Abstract Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare system. Online patient data processing from remote places may lead to severe privacy problems. Moreover, the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to offloading of live patient data to remote cloud servers. Solve the privacy problem. The proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption schemes. It can help maintain the privacy preservation and confidentiality of patients’ medical data during diagnosis of Parkinson’s disease. In addition, the energy and delay aware computational offloading… More >

RAHAT ALI¹, AFTAB ALAM², SATYENDRA K. RAJPUT³, RAZI AHMAD^4,*

BIOCELL, Vol.46, No.12, pp. 2681-2694, 2022, DOI:10.32604/biocell.2022.021224

Abstract Parkinson’s disease (PD) is an age-related neurodegenerative ailment that affects dopamine-producing neurons in a specific area of the brain called the substantia nigra of the ventral midbrain. It is clinically characterized by movement disorder and marked with unusual synaptic protein alpha-synuclein accumulation in the brain. To date, only a few Food and Drug Administration (FDA) approved drugs are available on the market for the treatment of PD. Nonetheless, these drugs show parasympathomimetic related adverse events and remarkably higher toxicity; hence, it is important to find more efficacious molecules to treat PD. In our study, We chosen 22 natural compounds as… More >

Zhengshu Zhou^1,*, Shunya Yamada², Yousuke Watanabe², Hiroaki Takada^1,2

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2109-2127, 2023, DOI:10.32604/csse.2023.029005

Abstract Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians’ sudden appearance in the vehicle’s path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision… More >

Ashit Kumar Dutta^1,*, Nazik M. A. Zakari², Yasser Albagory³, Abdul Rahaman Wahab Sait⁴

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2195-2207, 2023, DOI:10.32604/csse.2023.026461

Abstract Parkinson’s disease (PD) is one of the primary vital degenerative diseases that affect the Central Nervous System among elderly patients. It affect their quality of life drastically and millions of seniors are diagnosed with PD every year worldwide. Several models have been presented earlier to detect the PD using various types of measurement data like speech, gait patterns, etc. Early identification of PD is important owing to the fact that the patient can offer important details which helps in slowing down the progress of PD. The recently-emerging Deep Learning (DL) models can leverage the past data to detect and classify… More >

M. Mohamed Iqbal^1,*, K. Latha²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1831-1842, 2023, DOI:10.32604/iasc.2023.029036

Abstract The public is increasingly using social media platforms such as Twitter and Facebook to express their views on a variety of topics. As a result, social media has emerged as the most effective and largest open source for obtaining public opinion. Single node computational methods are inefficient for sentiment analysis on such large datasets. Supercomputers or parallel or distributed processing are two options for dealing with such large amounts of data. Most parallel programming frameworks, such as MPI (Message Processing Interface), are difficult to use and scale in environments where supercomputers are expensive. Using the Apache Spark Parallel Model, this… More >

G. Prema Arokia Mary^1,*, N. Suganthi²

Computer Systems Science and Engineering, Vol.43, No.1, pp. 333-345, 2022, DOI:10.32604/csse.2022.021164

Abstract Parkinson’s disease (PD) is a neurodegenerative disease in the central nervous system. Recently, more researches have been conducted in the determination of PD prediction which is really a challenging task. Due to the disorders in the central nervous system, the syndromes like off sleep, speech disorders, olfactory and autonomic dysfunction, sensory disorder symptoms will occur. The earliest diagnosing of PD is very challenging among the doctors community. There are techniques that are available in order to predict PD using symptoms and disorder measurement. It helps to save a million lives of future by early prediction. In this article, the early… More >

Zhihan Lv^1,*, Jinkang Guo²

International Journal of Mental Health Promotion, Vol.24, No.3, pp. 287-310, 2022, DOI:10.32604/ijmhp.2022.019829

Abstract The present work investigates the application of virtual reality (VR) technology to neurorehabilitation. By consulting a wealth of data, the advantages of VR in neurorehabilitation are introduced, followed by the application status of VR in the rehabilitation of stroke patients, Parkinson’s patients, mental and psychological diseases. Besides, many research experiments on the application of VR technology in rehabilitation medicine at the present stage are investigated. The results indicate that compared with traditional balance training, the VR-based neurological rehabilitation training method can more effectively ease the tilt degree and strengthen the trunk control ability and balance function of patients with post-stroke… More >

Ahmed S. Almasoud¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Abubakar Elsafi⁵, Mesfer Al Duhayyim⁶, Ishfaq Yaseen⁷, Manar Ahmed Hamza^7,*, Abdelwahed Motwakel⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 871-886, 2022, DOI:10.32604/cmc.2022.024596

Abstract Early detection of Parkinson's Disease (PD) using the PD patients’ voice changes would avoid the intervention before the identification of physical symptoms. Various machine learning algorithms were developed to detect PD detection. Nevertheless, these ML methods are lack in generalization and reduced classification performance due to subject overlap. To overcome these issues, this proposed work apply graph long short term memory (GLSTM) model to classify the dynamic features of the PD patient speech signal. The proposed classification model has been further improved by implementing the recurrent neural network (RNN) in batch normalization layer of GLSTM and optimized with adaptive moment… More >