A Plantar Pressure Detection and Gait Analysis System Based on Flexible Triboelectric Pressure Sensor Array and Deep Learning

Small, Год журнала: 2024, Номер unknown

Опубликована: Окт. 30, 2024

Abstract Gait detection is essential for the assessment of human health status and early diagnosis diseases. The current gait analysis systems are bulky, limited in scope use, cause interference with movement measured person. Hence, it necessary to develop a wearable system that soft, breathable, lightweight, self‐powered. Here, plantar pressure sensor array based on flexible triboelectric (FTPS) developed. Soft, electrospinning nanofiber film excellent properties used as sensor, achieving high sensitivity 45.1 mV kPa −1 range 40–200 19.4 200–400 kpa. 32 FTPSs integrated into an intelligent insole, which has characteristics easy production, good air permeability, long‐time stability, no external power supply, etc. Based long short‐term memory artificial neural network deep learning model, accuracy judgment can reach 94.23%. This work provides feasible solution real‐time detection, will have potential applications disease.

Язык: Английский

---

Hypoxia Sensing and Responses in Parkinson’s Disease

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(3), С. 1759 - 1759

Опубликована: Фев. 1, 2024

Parkinson’s disease (PD) is associated with various deficits in sensing and responding to reductions oxygen availability (hypoxia). Here we summarize the evidence pointing a central role of hypoxia PD, discuss relation dependence pathological hallmarks including mitochondrial dysfunction, dopaminergic vulnerability, alpha-synuclein-related pathology, highlight link cellular systemic sensing. We describe cases suggesting that may trigger Parkinsonian symptoms but also emphasize endogenous systems protect from can be harnessed PD. Finally, provide examples preclinical clinical research substantiating this potential.

Язык: Английский

---

Predicting stress levels using physiological data: Real-time stress prediction models utilizing wearable devices

AIMS neuroscience, Год журнала: 2024, Номер 11(2), С. 76 - 102

Опубликована: Янв. 1, 2024

<abstract> <p>Stress has emerged as a prominent and multifaceted health concern in contemporary society, manifesting detrimental effects on individuals' physical mental well-being. The ability to accurately predict stress levels real time holds significant promise for facilitating timely interventions personalized management strategies. increasing incidence of stress-related issues highlights the importance thoroughly understanding prediction mechanisms. Given that is contributing factor wide array problems, objectively assessing crucial behavioral physiological studies. While numerous studies have assessed controlled environments, objective evaluation everyday settings still needs be explored, primarily due contextual factors limitations self-report adherence. This short review explored emerging field real-time prediction, focusing utilizing data collected by wearable devices. Stress was examined from comprehensive standpoint, acknowledging its both synthesized existing research development application models, underscoring advancements, challenges, future directions this rapidly evolving domain. Emphasis placed examining critically evaluating literature analysis, devices monitoring. synthesis findings aimed contribute better potential technology predicting time, thereby informing design effective approaches.</p> </abstract>

Язык: Английский

---

Listerin promotes α-synuclein degradation to alleviate Parkinson’s disease through the ESCRT pathway

Science Advances, Год журнала: 2025, Номер 11(7)

Опубликована: Фев. 12, 2025

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the progressive accumulation of abnormal α-synuclein (α-syn) within dopaminergic neurons in substantia nigra region brain. Despite excessive α-syn being key to pathogenesis PD, mechanisms governing its clearance remain elusive. In this study, we found that endosomal sorting complex required for transport (ESCRT) system plays crucial role capturing and facilitating degradation ubiquitinated α-syn. The E3 ubiquitin ligase Listerin was promote K27-linked polyubiquitination α-syn, directing it endosome subsequent degradation. We showed deletion gene exacerbates progression mouse model whereas overexpression effectively mitigates PD mice. Consequently, our study reveals mechanism identifies as promising therapeutic target treatment PD.

Язык: Английский

---

The Power of Exercise: Unlocking the biological Mysteries of Peripheral-Central crosstalk in Parkinson’s disease

Journal of Advanced Research, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

---

Epigenetic regulation of iron metabolism and ferroptosis in Parkinson’s disease: Identifying novel epigenetic targets

Acta Pharmacologica Sinica, Год журнала: 2025, Номер unknown

Опубликована: Март 11, 2025

Язык: Английский

---

Digital Biomarkers for Parkinson's Disease: A Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait (Preprint)

Journal of Medical Internet Research, Год журнала: 2025, Номер 27, С. e71560 - e71560

Опубликована: Март 19, 2025

With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore current research trends and key areas focus. This study aimed comprehensively evaluate status, hot spots, future global PD biomarker provide a systematic review deep learning models for freezing gait (FOG) biomarkers. used bibliometric analysis based on Web Science Core Collection database conduct comprehensive multidimensional landscape After identifying also followed PRISMA-ScR (Preferred Reporting Items Systematic Reviews Meta-Analyses Extension Scoping Reviews) guidelines scoping FOG from 5 databases: Science, PubMed, IEEE Xplore, Embase, Google Scholar. A total 750 studies were included analysis, 40 review. The revealed growing number related publications, with 3700 researchers contributing. Neurology had highest average annual participation rate (12.46/19, 66%). United States contributed most (192/1171, 16.4%), 210 participating institutions, which was among all countries. In FOG, accuracy 0.92, sensitivity 0.88, specificity 0.90, area under curve 0.91. addition, 31 (78%) indicated that best primarily convolutional neural networks or networks-based architectures. Research is currently at stable stage development, widespread interest countries, researchers. However, challenges remain, including insufficient interdisciplinary interinstitutional collaboration, as well lack corporate funding projects. Current focus motor-related studies, particularly monitoring. still external validation standardized performance reporting. Future will likely progress toward deeper applications artificial intelligence, enhanced different data types, exploration broader range symptoms. Open Foundation (OSF Registries) OSF.IO/RG8Y3; https://doi.org/10.17605/OSF.IO/RG8Y3.

Язык: Английский

---

Dual-response fluorescent probe for real-time super-resolution imaging of mitochondrial nucleoprotein dynamics in Parkinson's disease

Sensors and Actuators B Chemical, Год журнала: 2025, Номер unknown, С. 137703 - 137703

Опубликована: Март 1, 2025

Язык: Английский

---

Gait detection of lower limb exoskeleton robot integrating visual perception and geometric features

Intelligent Service Robotics, Год журнала: 2025, Номер unknown

Опубликована: Апрель 23, 2025

Язык: Английский

---

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait (Preprint)

Опубликована: Янв. 21, 2025

With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore current research trends and key areas focus. This study aimed comprehensively evaluate status, hot spots, future global PD biomarker provide a systematic review deep learning models for freezing gait (FOG) biomarkers. used bibliometric analysis based on Web Science Core Collection database conduct comprehensive multidimensional landscape After identifying also followed PRISMA-ScR (Preferred Reporting Items Systematic Reviews Meta-Analyses Extension Scoping Reviews) guidelines scoping FOG from 5 databases: Science, PubMed, IEEE Xplore, Embase, Google Scholar. A total 750 studies were included analysis, 40 review. The revealed growing number related publications, with 3700 researchers contributing. Neurology had highest average annual participation rate (12.46/19, 66%). United States contributed most (192/1171, 16.4%), 210 participating institutions, which was among all countries. In FOG, accuracy 0.92, sensitivity 0.88, specificity 0.90, area under curve 0.91. addition, 31 (78%) indicated that best primarily convolutional neural networks or networks–based architectures. Research is currently at stable stage development, widespread interest countries, researchers. However, challenges remain, including insufficient interdisciplinary interinstitutional collaboration, as well lack corporate funding projects. Current focus motor-related studies, particularly monitoring. still external validation standardized performance reporting. Future will likely progress toward deeper applications artificial intelligence, enhanced different data types, exploration broader range symptoms. Open Foundation (OSF Registries) OSF.IO/RG8Y3; https://doi.org/10.17605/OSF.IO/RG8Y3

Язык: Английский

---