project | CV_YIMING_ZHONG

Contactless Smart Infant Sleep Monitoring System

Sat, 01 Feb 2025 00:00:00 +0000

Developed a multispectral physiological imaging system for precise, contactless monitoring of infant vital signs, in collaboration with a leading hospital in Wenzhou.

Established an interpretable video-based sleep/wake classification model to enhance monitoring accuracy from consumer-grade to clinical-grade standards.

Leveraged ECG and PPG signals to extract and validate infant motion metrics for preliminary sleep analysis.

Deployed open-source human pose estimation and optical flow algorithms to compute key-point motion features, confirming feasibility of camera-based polysomnography (PSG) for infant sleep staging.

Conducted camera-based PSG monitoring on 100 infants to establish normative sleep-stage benchmarks.

Extracted limb movement coordination and intensity features from video data, applying SVM and Random Forest classifiers for binary and multi-class sleep-stage classification.

Applied DL algorithms (LSTM, Transformer) to improve the accuracy of infant sleep stage classification.

SSVEP-based BCI Robotic Car Control System with MATLAB

Tue, 05 Nov 2024 00:00:00 +0000

Collected EEG signals from occipital regions using gold cup electrodes and a Cyton board (250 Hz).

Applied Butterworth filters for noise reduction and extracted key EEG components (4–35 Hz).

Implemented and compared CCA and FFT methods to decode SSVEP frequencies with high accuracy.

Transmitted motion commands via Bluetooth to demonstrate reliable and precise human-machine interaction.

Reference: Li, M.; He, D.; Li, C.; Qi, S. Brain–Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance. Brain Sci. 2021, 11, 450. https://doi.org/10.3390/brainsci11040450

MATLAB-based ECG Signal Acquisition and Processing

Thu, 05 Sep 2024 00:00:00 +0000

Developed a user-friendly prototype for heart health monitoring, emphasizing real-time analysis and ease of use.

Built a differential circuit and analogue filtering system for accurate ECG signal measurement.

Integrated the AD8232 Heart Rate Monitor and MATLAB to process ECG signals via an NI USB 6009 module.

Configured a MATLAB GUI for real-time sampling, noise removal, and enhanced waveform analysis.

Multidimensional Video-based Contactless Infant Seizure Monitoring

Mon, 01 Apr 2024 00:00:00 +0000

Developed a real-time monitoring and prediction algorithm for infant seizures in collaboration with a a leading tertiary hospital in Guangzhou, aiming to establish a low-cost, contactless detection system to mitigate resource limitations and inconsistencies in seizure diagnosis quality.

Preprocessed raw ECG signals to extract heart rate and calculate heart rate variability (HRV).

Utilized remote photoplethysmography (rPPG) to extract heart rate and HRV from video data for non-invasive physiological monitoring.

Applied optical flow techniques to analyze global and skin-region motion in vEEG videos.

Deployed open-source human pose estimation tools to detect infant keypoints and compute motion intensity.

Analyzed limb movement intensity using cross-correlation and Pearson correlation coefficients to integrate motion and physiological signals.

Introduced a camera-based solution for NICU settings, enabling contactless monitoring of infant motion and vital signs with improved precision and efficiency.