Parkinson’s Disease Classification and Medication Adherence Monitoring Using Smartphone-based Gait Assessment and Deep Reinforcement Learning Algorithm

Salgueiro, Armando de Jesús Plasencia; Shichkina, Yulia; García, Arlety García; Rodríguez, Lynnette González

doi:10.1016/j.procs.2021.04.175

Cited by 13 publications

(2 citation statements)

References 6 publications

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“…Taking MSO-VGG19BN as an example, we first remove the fully connected layer at the end of the VGG19BN network. The fully connected layer can only accept a fixed size input, and it will not work once the image size changes [ 14 ]. By removing the fully connected layer, the proposed network can accept images of any size as input.…”

Section: Methodsmentioning

confidence: 99%

Design of an Incremental Music Teaching and Assisted Therapy System Based on Artificial Intelligence Attention Mechanism

Liu

2022

Occupational Therapy International

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With the continuous updating and advancement of artificial intelligence technology, it gradually begins to shine in various industries, especially playing an increasingly important role in incremental music teaching and assisted therapy systems. This study designs artificial intelligence models from the perspectives of attention mechanism, contextual information guidance, and distant dependencies combined with incremental music teaching for the segmentation of MS (multiple sclerosis) lesions and achieves the automatic and accurate segmentation of MS lesions through the multidimensional analysis of multimodal magnetic resonance imaging data, which provides a basis for physicians to quantitatively analyze MS lesions, thus assisting them in the diagnosis and treatment of MS. To address the highly variable characteristics of MS lesion location, size, number, and shape, this paper firstly designs a 3D context-guided module based on Kronecker convolution to integrate lesion information from different fields of view, starting from lesion contextual information capture. Then, a 3D spatial attention module is introduced to enhance the representation of lesion features in MRI images. The experiments in this paper confirm that the context-guided module, cross-dimensional cross-attention module, and multidimensional feature similarity module designed for the characteristics of MS lesions are effective, and the proposed attentional context U-Net and multidimensional cross-attention U-Net have greater advantages in the objective evaluation index of lesion segmentation, while being combined with the incremental music teaching approach to assist treatment, which provides a new idea for the intelligent assisted treatment approach. In this paper, from algorithm design to experimental validation, both in terms of accuracy, the operational difficulty of the experiment, consumption of arithmetic power, and time cost, the unique superiority of the artificial intelligence attention-based combined with incremental music teaching adjunctive therapy system proposed in this paper can be seen in the MS lesion segmentation task.

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Section: Methodsmentioning

confidence: 99%

Design of an Incremental Music Teaching and Assisted Therapy System Based on Artificial Intelligence Attention Mechanism

Liu

2022

Occupational Therapy International

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“…Parkinson's disease is a degenerative disorder of slow progress of the nervous system caused by the lack of levels of dopamine, which can provoke uncontrolled involuntary movements of the body and psychological affections [2].…”

Section: Introductionmentioning

confidence: 99%

A Simulation Model of a Blockchain-Based Decentralized Patient Information Exchange System for Parkinson’s Disease Patients

Salgueiro¹,

García²

2023

Blockchain Applications - Transforming Industries, Enhancing Security, and Addressing Ethical Considerations

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Parkinson’s disease (PD) is a progressive disorder of slow progress of the nervous system produced by the absence of levels of dopamine, which can incite unrestrained instinctive movements of the body and psychological affections. For the development of a practical, low-cost, and general diagnosis system of the symptoms to support PD patients, the implementation of an IoT health monitoring system that uses smartphones for data collection is necessary. However, data can be processed in Cloud Computing (CC) for analysis and comparison, but to reduce the latency of retrieving data from sensitive applications, Fog Computing (FC) plays a vital role. Nevertheless, these technologies IoT, CC, and FC have several limitations and are vulnerable to security threats. Blockchain technology enhances IoT challenges in a network in terms of security and availability. This chapter implemented a Decentralized IoT Fog-based Solutions and Blockchain using Ethereum Smart Contract for the authentication system. The smart contract is programmed using Solidity to allow Things to communicate with each other automatically without intermediaries and to store data in a public/private blockchain. The validation of the system was simulated them using the simulations tools Cisco Packet Tracer, iFogSim, and Remix Ethereum. The obtained results proved the feasibility of the proposed system.

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Freezing of gait in Parkinson’s disease: Classification using computational intelligence

Beigi,

Nóbrega,

Houghten

et al. 2023

Biosystems

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Parkinson’s Disease Classification and Medication Adherence Monitoring Using Smartphone-based Gait Assessment and Deep Reinforcement Learning Algorithm

Cited by 13 publications

References 6 publications

Design of an Incremental Music Teaching and Assisted Therapy System Based on Artificial Intelligence Attention Mechanism

Design of an Incremental Music Teaching and Assisted Therapy System Based on Artificial Intelligence Attention Mechanism

A Simulation Model of a Blockchain-Based Decentralized Patient Information Exchange System for Parkinson’s Disease Patients

Freezing of gait in Parkinson’s disease: Classification using computational intelligence

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