About me: Machine Learning, DSP & Image Processing; biomedical signal processing, IoT; Process control, Exploratory data analysis

My area of ​​interest:

├── [Biomedical Signal Processing]                 ( from embeded  do Machine learning solutions) 
│      ├── ECG DSP                                -> ISO EN 60601-2-47,-2-27, -2-25 +ISO 14971 
│      ├── EEG DSP                                -> events/feature extraction  
│      ├── other: SPO2,blood glucose dsp     
│      ├── Immage processing:  classification, feature extraction  
│      
├─── [Control Design and process simulation]
|      ├──Nonlinear dynamic systems modeling and simulation 
|      ├──Advanced control algorithms             
|      ├──identification & optimization          
|      ├──Phsical process modeling                -> Mechanics, mechatronics systems, Vibration analysis, dynamic simulations
|    
|
├─── [DSP and IP procesing]
|      ├─data acquisition and analysis,statistical and spectral analysis     
|      ├── filters design and simulations         
|      ├── object feature extraction, detection and tracking                   
|      ├─ audio processing   
|
├─── [Machine learning and Deep learning]          (Supervised vs Unsupervised methods)      
|      ├─ Time series forecasting
|      ├─ classification, feature extraction
|      ├─ RBF and MLP neuron net 
|
├─── [ embedded systems ]          
|      ├─ ESP32/RPI2040 + IOT, RP2040, Raspbery PI (mostly DSP, Control algorithms, neural networks (mlp, rbf) in indetification and control adaptation algorithms)
|      ├─ mechatronic and sensors.
|      ├─  
└──  

Below some examplse snapshots (not all projects/work is presented):

	seizure episodes detection and attack predictions.

	Lidar Data/Immage segmentations - feature image segmentation for lakes, rivers, roads ( length, area calculation)

	Damage detection/segmentation on bandage line production - separate parameters configurations for burst material and double interlacing -segmentation in in the presence of heterogeneous light (shadows)

	labview app for keller pressure sensors testing Modbus RTU, noise filters design, full settings and sensor control

Universal PID Controller platform: - platforms/interfaces: easy implementation as hardware/soft platform (ESP MCU family, Raspberry PI, web server,(4 or 5 key keyboard, OLED (0.91/0.92) with multilevel menu and multiple views, UART inteface for HMI Control/), - PID, On-Off control, antiwind-up, Man/Auto bumpless selector -Setpoint processing: user/external setting, Curve generation, alarms -PV processig, thermocouple K,J calculation, alarms, - CV processing: PWM , Relay output, alarms. See:library Repo.

	ECG WIDGET MONITOR - just standatd ECG monitor with BPM indication, configurable for multi-bio real time signal visualisation and processing.