PD Disease State Assessment in Naturalistic Environments Using Deep Learning

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A fast learning algorithm for deep belief nets

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A tutorial on human activity recognition using body-worn inertial sensors

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New types of deep neural network learning for speech recognition and related applications: an overview

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Monitoring Motor Fluctuations in Patients With Parkinson's Disease Using Wearable Sensors

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Automated vision-based analysis of levodopa-induced dyskinesia with deep learning

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Marfusion: An Attention-Based Multimodal Fusion Model for Human Activity Recognition in Real-World Scenarios

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Efficient human activity recognition: A deep convolutional transformer-based contrastive self-supervised approach using wearable sensors

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A Multi-Layer Gaussian Process for Motor Symptom Estimation in People With Parkinson's Disease

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Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson’s Disease Classification of Gait Patterns

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An Auxiliary Diagnostic System for Parkinson’s Disease Based on Wearable Sensors and Genetic Algorithm Optimized Random Forest

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Real-time sepsis severity prediction on knowledge graph deep learning networks for the intensive care unit

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Abnormal Behaviour Detection for Dementia Sufferers via Transfer Learning and Recursive Auto-Encoders

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Continuous and Unconstrained Tremor Monitoring in Parkinson’s Disease Using Supervised Machine Learning and Wearable Sensors

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Unsupervised Learning for Product Use Activity Recognition: An Exploratory Study of a “Chatty Device”

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CXCR4 knockout induces neuropathological changes in the MPTP-lesioned model of Parkinson's disease

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Comparing laboratory and in-the-wild data for continuous Parkinson’s Disease tremor detection

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Detection of Dementia-Related Abnormal Behaviour Using Recursive Auto-Encoders

Arifoğlu, D., Wang, Y., & Bouchachia, A. (2021) · Sensors · doi:10.3390/s21010260 · Cited by 12

Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and VisualizationPreprint

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Activity-Aware Deep Cognitive Fatigue Assessment using Wearables

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Contribution of Application of Deep Learning Approaches on Biomedical Data in the Diagnosis of Neurological Disorders: A Review on Recent Findings

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An Attention-Based Deep Learning Method for Schizophrenia Patients Classification Using DNA Methylation Data

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Human Activity Recognition in Smart Cities from Smart Watch Data using LSTM Recurrent Neural Networks

Kandpal, M., Sharma, B., Barik, R. K., Chowdhury, S., Patra, S. S., & Dhaou, I. B. (2023) · International Conference on Advanced Innovations in Smart Cities (ICAISC) · doi:10.1109/icaisc56366.2023.10085688 · Cited by 9

Monitoring Parkinson's Disease Progression Using Behavioural Inferences, Mobile Devices and Web Technologies

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A C-LSTM Neural Network for Human Activity Recognition Using Wearables

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Towards Automated Fatigue Assessment using Wearable Sensing and Mixed-Effects Models

Bai, Y., Guan, Y., Shi, J. Q., & Ng, W. (2021) · International Symposium on Wearable Computers · doi:10.1145/3460421.3480429 · Cited by 8

Transforming Healthcare: Advancements, Applications, and Future Directions of Machine Learning

Puli, S. K., & Usha, P. (2024) · International Conference on Smart Computing and Communications (ICSCC) · doi:10.1109/icscc62041.2024.10690530 · Cited by 8

Designing compact features for remote stroke rehabilitation monitoring using wearable accelerometers

Chen, X., Guan, Y., Shi, J. Q., Du, X., & Eyre, J. A. (2023) · CCF Transactions on Pervasive Computing and Interaction · doi:10.1007/s42486-022-00124-3 · Cited by 8

Deep Learning for Sensor-Based Activity Recognition: Recent Trends

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CogAx: Early Assessment of Cognitive and Functional Impairment from Accelerometry

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Learning Representations of Missing Data for Predicting Patient OutcomesPreprint

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Collecting, Integrating and Processing IoT Sensor Data on Edge Devices for PD Monitoring: A Scoping Review

Stefanou, E. E., Bitilis, P., Bouchouras, G., & Kotis, K. (2025) · Applied Sciences · doi:10.3390/app151910541 · Cited by 7

Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach

Evers, L. J. W., Raykov, Y. P., Heskes, T., Krijthe, J. H., Bloem, B. R., & Little, M. A. (2025) · Sensors · doi:10.3390/s25020366 · Cited by 6

ALAE-TAE-CutMix+: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors

Ahmad, N., & Leung, H.-F. (2023) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom56429.2023.10099138 · Cited by 6

Tutorial on Deep Learning for Human Activity RecognitionPreprint

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Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors

Airaksinen, M., Vanhatalo, S., & Räsänen, O. J. (2023) · Sensors · doi:10.3390/s23073773 · Cited by 5

Reconstruction of Total Solar Irradiance by Deep Learning

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To Transfer or Not to Transfer and Why? Meta-Transfer Learning for Explainable and Controllable Cross-Individual Activity Recognition

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Abnormal Activity Detection for the Elderly People using ConvLSTM Autoencoder

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Big Data and Data Science Applications for Independent and Healthy Living

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SMART: Emerging Activity Recognition with Limited Data for Multi-modal Wearable Sensing

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Attend And Discriminate: Beyond the State-of-the-Art for Human Activity Recognition using Wearable SensorsPreprint

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Qualitative Analysis of Techniques for Device-Free Human Activity Recognition

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Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition

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Automated General Movement Assessment for Perinatal Stroke Screening in Infants

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DeepLite: Real-Time Deep Learning Framework for Neighborhood Analysis

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Wearable-based Mediation State Detection in Individuals with Parkinson's DiseasePreprint

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Walking-posture Classification from Single-acceleration-sensor Data using Deep Learning

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Tragbare und aktiv vom Parkinson-Patienten genutzte Technologie im häuslichen Umfeld: Was bringt die Zukunft?

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Smart Assisted Living: Toward An Open Smart-Home Infrastructure

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A Convolutional Neural Network Approach for Quantification of Tremor Severity in Neurological Movement Disorders

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Toward Data Augmentation and Interpretation in Sensor-Based Fine-Grained Hand Activity Recognition

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Machine learning for healthcare using wearable sensors

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Automated Stroke Rehabilitation Assessment using Wearable Accelerometers in Free-Living Environments.Preprint

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Guided-GAN: Adversarial Representation Learning for Activity Recognition with WearablesPreprint

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Prediction of Autoimmune Disease using Ensemble Machine Learning Approaches

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Novel analytics in the management of movement disorders

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S2C‐HAR: A Semi‐Supervised Human Activity Recognition Framework Based on Contrastive Learning

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Predicting disease outcomes from remote monitoring using machine learning: a systematic review

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Activity Recognition Analysis System and Application Based on Convolutional Neural Network

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Walking-posture Classification from Single-acceleration-sensor Data using Deep Learning and its Evaluation

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Improved Usability of IOT Devices in Healthcare Using Big Data Analysis

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Functional Data and Long Short-Term Memory Networks for Diagnosis of Parkinson’s Disease

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Case Study: Deep Convolutional Networks in Healthcare

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Pervasive Sensing

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BlobSnake: gamification of feature extraction for 'plug and play' human activity recognition

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Combining Multiple Concurrent Physiological Streams to Assessing Patients Condition.

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A unified algorithm framework for quality control of sensor data for behavioural clinimetric testingPreprint

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Bedeutung der Mobilitätsmessung — Zukunftsmusik oder sinnvoll?

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Improved Humanoid Gait Using Learning-Based Analysis of a New Wearable 3D Force System: Work Programme

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Using LSTM for Detection of Wrist Related Disorders

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Continuous Parkinsonian Tremor Estimation Using Motion Data

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Using off-the-shelf data-human interface platforms: traps and tricks

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Developing Clinical Decision Support Systems for Sepsis Prediction Using Temporal and Non-Temporal Machine Learning Methods

Gupta, A. (2019) · SHAREOK (University of Oklahoma; Oklahoma State University; Central Oklahoma University)

Inertial Sensor Data To Image Encoding For Human Action RecognitionPreprint

Ahmad, Z., & Khan, N. (2023) · doi:10.32920/22734293

Progress on Computational Ethology

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An Intrinsic Human Physical Activity Recognition from Fused Motion Sensor Data using Bidirectional Gated Recurrent Neural Network in Healthcare

Stephen, O., Madanian, S., & Nguyen, M. (2022) · International Conference on e-Business · doi:10.5220/0011296400003280

Analysis of Parkinson’s disease based on mobile application

Torres-Ruiz, M. J., Guzmán, G., Moreno-Ibarra, M., & Acosta-Arenas, A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822060-3.00001-2

Inertial Sensor Data To Image Encoding For Human Action RecognitionPreprint

Ahmad, Z., & Khan, N. (2023) · doi:10.32920/22734293.v1

Multimodal Sensor Fusion Frameworks With Application to Human Action Recognition

Ahmad, Z. (2024) · doi:10.32920/25234624.v1

Enhancing Squad Rating with Emotional Dynamic Parameters Influencing Adaptive Gameplay Strategies

Sreenarayanan, N. M., & Partheeban, N. (2025) · International Conference on Data Science and Business Systems (ICDSBS) · doi:10.1109/icdsbs63635.2025.11031553

A Deep Learning Framework for the Remote Detection of Parkinson’S Disease Using Smart-Phone Sensor Data

Prince, J., & Vos, M. D. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512972 · Cited by 53

PARQ: A Deep Learning Based Approach for Automatic Assessment of Motor Disease Severity in Parkinson’s Disease

Chakraborty, I. (2025) · Rice Research Repository (Rice University)

Assessment of Parkinson’s Disease At-home Using a Natural Interface Based System

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Wearable-Sensor-Based Weakly Supervised Parkinson’s Disease Assessment with Data Augmentation

Yue, P., Li, Z., Zhou, M., Wang, X., & Yang, P. (2024) · Sensors · doi:10.3390/s24041196 · Cited by 16

A Weakly Supervised Learning Framework for Parkinson’s Disease Assessment Using Wearable Sensor

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