HAND MOVEMENT DISORDERS TRACKING BY SMARTPHONE BASED ON COMPUTER VISION METHODS

Apple Machine Learning Research (n.d.). Deploying Transformers on the Apple Neural Engine [https://machinelearning.apple.com/research/neural-engine-transformers].
  Google Scholar

Apple Inc. (n.d.). Streaming Depth Data from the TrueDepth Camera. Apple Developer Documentation [https://developer.apple.com/documentation/avfoundation/additional_data_capture/streaming_depth_data_from_the_truedepth_camera].
  Google Scholar

Apple Developer Documentation. Streaming Depth Data from the TrueDepth Camera | Apple Developer Documentation [https://developer.apple.com/documentation/avfoundation/additional_data_capture/streaming_depth_data_from_the_truedepth_camera,2023] (accessed 3 Dec. 2023).
  Google Scholar

Assimp.org. The Asset-Importer Library Home [https://www.assimp.org] (accessed 3 Dec. 2023).
  Google Scholar

Avrunin O. G. et al.: Research Active Posterior Rhinomanometry Tomography Method for Nasal Breathing Determining Violations. Sensors 21, 2021, 8508.
  Google Scholar

Avrunin O. et al.: Improving the methods for visualization of middle ear pathologies based on telemedicine services in remote treatment. IEEE KhPI Week on Advanced Technology, KhPI Week, 2020, 347–350.
  Google Scholar

GitHub [https://github.com/googlesamples/mediapipe/tree/main/examples/hand_landmarker/ios] (accessed 19 Feb. 2024).
  Google Scholar

Google for Developers. Hand landmarks detection guide [https://developers.google.com/mediapipe/solutions/vision/hand _landmarker#model] (accessed 19 Feb. 2024).
  Google Scholar

Gupta S., White M.: Improved On-Device ML on Pixel 6, with Neural Architecture Search. Google Research Blog [https://blog.research.google/2021/11/improved-on-device-ml-on-pixel-6-with.html] (accessed 8 Nov. 2021).
  Google Scholar

Kim B., Neville Ch.: Accuracy and Feasibility of a Novel Fine Hand Motor Skill Assessment Using Computer Vision Object Tracking. Scientific Reports 13(1), 2023, 1–14 [https://doi.org/10.1038/s41598-023-29091-0].
  Google Scholar

Lin T.-Y. et al.: Feature Pyramid Networks for Object Detection [https://arxiv.org/pdf/1612.03144.pdf].
  Google Scholar

Liu W. et al.: SSD: Single Shot MultiBox Detector [https://arxiv.org/pdf/1512.02325.pdf].
  Google Scholar

Liang M. et al.: Deep Continuous Fusion for Multi-Sensor 3D Object Detection. 2020 [https://arxiv.org/abs/2012.10992] (accessed 19 Feb. 2024).
  Google Scholar

Liang M. et al.: Multi-Task Multi-Sensor Fusion for 3D Object Detection [https://openaccess.thecvf.com/content_CVPR_2019/papers/Liang_MultiTask_MultiSensor_Fusion_for_3D_Object_Detection_CVPR_2019_paper.pdf].
  Google Scholar

Muhammad B. S., Chai D.: RGB-D Data-Based Action Recognition: A Review. Sensors 21(12), 2021, 4246–4246 [https://doi.org/10.3390/s21124246].
  Google Scholar

On-Device, Real-Time Hand Tracking with MediaPipe [https://blog.research.google/2019/08/on-device-real-time-hand-tracking-with.html] (accessed 19 Feb. 2024).
  Google Scholar

Romanyuk O. et al.: A function-based approach to real-time visualization using graphics processing units. Proc. SPIE 11581, 2020, 115810E [https://doi.org/10.1117/12.2580212].
  Google Scholar

Selivanova K. Avrunin O.: Method of Hand Movement Disorders Determination based on the Surgeon's Laparoscopic Video Recording. 3rd KhPI Week on Advanced Technology – KhPIWeek, 2022, 1–4 [https://doi.org/10.1109/KhPIWeek57572.2022.9916457].
  Google Scholar

Selivanova K. et al.: The tracking system of a three-dimensional position of hand movement for tremor detection. Proc. SPIE 11581, 2020, 115810I [https://doi.org/10.1117/12.2580330].
  Google Scholar

Sokol Y. et al.: Using medical imaging in disaster medicine. IEEE 4th International Conference on Intelligent Energy and Power Systems, IEPS 2020, 2020, 287–290.
  Google Scholar

Taeger J. et al.: Utilization of Smartphone Depth Mapping Cameras for App-Based Grading of Facial Movement Disorders: Development and Feasibility Study. JMIR mHealth and uHealth 9(1), 2021, e19346 [https://doi.org/10.2196/19346].
  Google Scholar

Turlykozhayeva D. et al.: Routing Algorithm for Software Defined Network Based on Boxcovering Algorithm. 10th International Conference on Wireless Networks and Mobile Communications – WINCOM, 2023.
  Google Scholar

Tymkovych M. et al.: 3D scanning technologies by optical RealSense cameras for SIREN-based 3D hand representation. Proc. SPIE 12985, 2023, 129850O [https://doi.org/10.1117/12.3022737].
  Google Scholar

Urban S. et al.: On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different IPad Generations. 2022 [https://arxiv.org/abs/2201.10865] (accessed 26 Nov. 2023).
  Google Scholar

WójcikW. et al.: Information Technology in Medical Diagnostics II. Taylor & Francis Group. CRC Press, Balkema Book. London, 2019.
  Google Scholar

Wójcik W. et al.: Information Technology in Medical Diagnostics. CRC Press, 2017.
  Google Scholar

Zhang F. et al.: MediaPipe Hands: On-device Real-time Hand Tracking. 2006 [https://arxiv.org/abs/2006.10214].
  Google Scholar