IoT architecture for continuous long term monitoring: Parkinson’s Disease case study

d’Angelis, Onorato; Biase, Lazzaro di; Vollero, Luca; Merone, Mario

doi:10.1016/j.iot.2022.100614

Cited by 9 publications

(5 citation statements)

References 42 publications

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“…Clinical evaluation remains the gold standard for motor symptom identification and diagnosis in routine clinical practice. However, new technologies, like wearable motion sensor devices, are opening new ways not only for continuous at-home symptom monitoring [ 55 , 56 ] but also for the objective and quantitative description of PD motor symptoms [ 57 , 58 , 59 ], like tremors [ 60 , 61 , 62 , 63 ], bradykinesia [ 64 , 65 , 66 ], rigidity [ 66 , 67 , 68 , 69 ], gait, balance and postural issues [ 70 , 71 , 72 , 73 , 74 , 75 ], alongside motor complications like motor fluctuations and dyskinesias [ 76 , 77 , 78 ]. Additionally, among non-wearable sensors, video-based systems represent a reliable solution to assess the features of LIDs [ 79 ].…”

Section: Levodopa-induced Dyskinesiasmentioning

confidence: 99%

Section: Objective Lid Monitoringmentioning

confidence: 99%

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Levodopa-Induced Dyskinesias in Parkinson’s Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Biase

Pecoraro

Carbone

et al. 2023

JCM

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Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson’s disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.

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Section: Levodopa-induced Dyskinesiasmentioning

confidence: 99%

Section: Objective Lid Monitoringmentioning

confidence: 99%

Levodopa-Induced Dyskinesias in Parkinson’s Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Biase

Pecoraro

Carbone

et al. 2023

JCM

Self Cite

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“…Different strategies have been explored to characterize PD features in a non-invasive way. One first approach is to follow the clinical diagnostic pathway trying to make clinical evaluations of motor symptoms more objective and quantitative, through a motion analysis technique able to characterize PD motor symptoms [ 4 , 5 , 6 ], such as bradykinesia [ 7 , 8 , 9 ], tremors [ 10 , 11 , 12 , 13 ], rigidity [ 9 , 14 , 15 , 16 ], and axial symptoms, such as gait, balance, and postural issues [ 17 , 18 , 19 , 20 , 21 , 22 ], also with the support of machine learning algorithms [ 23 , 24 , 25 , 26 , 27 ]. Another possible approach is to explore the brain activities that underly and determine the PD symptoms, which are characterized by pathological oscillatory activities [ 28 , 29 ] and have been widely used to manage therapy, such as deep brain stimulation [ 30 , 31 ], but can be used also as a proxy for PD neurophysiology biomarkers identification.…”

Section: Introductionmentioning

confidence: 99%

Quantitative High Density EEG Brain Connectivity Evaluation in Parkinson’s Disease: The Phase Locking Value (PLV)

Biase

Ricci

Caminiti

et al. 2023

JCM

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Introduction: The present study explores brain connectivity in Parkinson’s disease (PD) and in age matched healthy controls (HC), using quantitative EEG analysis, at rest and during a motor tasks. We also evaluated the diagnostic performance of the phase locking value (PLV), a measure of functional connectivity, in differentiating PD patients from HCs. Methods: High-density, 64-channels, EEG data from 26 PD patients and 13 HC were analyzed. EEG signals were recorded at rest and during a motor task. Phase locking value (PLV), as a measure of functional connectivity, was evaluated for each group in a resting state and during a motor task for the following frequency bands: (i) delta: 2–4 Hz; (ii) theta: 5–7 Hz; (iii) alpha: 8–12 Hz; beta: 13–29 Hz; and gamma: 30–60 Hz. The diagnostic performance in PD vs. HC discrimination was evaluated. Results: Results showed no significant differences in PLV connectivity between the two groups during the resting state, but a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. Comparing the resting state versus the motor task for each group, only HCs showed a higher PLV connectivity in the delta band during motor task. A ROC curve analysis for HC vs. PD discrimination, showed an area under the ROC curve (AUC) of 0.75, a sensitivity of 100%, and a negative predictive value (NPV) of 100%. Conclusions: The present study evaluated the brain connectivity through quantitative EEG analysis in Parkinson’s disease versus healthy controls, showing a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. This neurophysiology biomarkers showed the potentiality to be explored in future studies as a potential screening biomarker for PD patients.

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“…The Internet of Things (IoT) and the smartphone markets are driving this trend, for instance, from handled devices to medical applications. [ 1–5 ] Further, the request for miniaturized electronic devices and components able to operate in harsh environmental conditions such as high temperatures, mechanical vibrations, and in the presence of chemicals is constantly increasing. [ 6–8 ] Printed circuit boards (PCBs) are getting miniaturized since passive components are moving towards the 01005‐packaging Surface Mount Devices (SMD) standard, and passive components are the ones occupying the larger percentage of the PCB itself.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Laser‐Induced Graphene Electrodes for High Voltage and Highly Stable Microsupercapacitors

Zaccagnini,

Tien,

Baudino

et al. 2023

Adv Materials Technologies

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Microsupercapacitors (µSCs) have received a lot of interest for their possible use in miniaturized electronics and in the field of the Internet of Things (IoT) to power distributed sensors. µSCs fill the gap between batteries and traditional capacitors, providing high power densities and acceptable energy densities to fulfill onboard power supply requirements, coupled with quick charge/discharge rates and extended lifetime. Charge balancing of µSCs is not a standard practice, although the optimization of electrodes can provide beneficial effects on the electrochemical performance and stability of the device. In this work, a charge‐balanced double‐layer µSC based on laser‐induced graphene (LIG) with [PYR14][TFSI] as an ionic liquid electrolyte is presented for the first time. The optimized device shows an improvement in terms of the increased lifetime of a factor of four and its energy efficiency is raised above 80%.

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IoT architecture for continuous long term monitoring: Parkinson’s Disease case study

Cited by 9 publications

References 42 publications

Levodopa-Induced Dyskinesias in Parkinson’s Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Levodopa-Induced Dyskinesias in Parkinson’s Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Quantitative High Density EEG Brain Connectivity Evaluation in Parkinson’s Disease: The Phase Locking Value (PLV)

Optimization of Laser‐Induced Graphene Electrodes for High Voltage and Highly Stable Microsupercapacitors

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