<div id="top"></div>
<!-- PROJECT SHIELDS -->
[![Contributors][contributors-shield]][contributors-url]
[![Forks][forks-shield]][forks-url]
[![Stargazers][stars-shield]][stars-url]
[![Issues][issues-shield]][issues-url]
[![MIT License][license-shield]][license-url]
<!-- TABLE OF CONTENTS -->
<details>
<summary>Table of Contents</summary>
<ol>
<li><a href="#about-the-project">About The Project</a></li>
<li><a href="#donation">Donation</a></li>
<li><a href="#components">Components</a></li>
<li><a href="#roadmap">Roadmap</a></li>
<li><a href="#pictures">Pictures</a></li>
<li><a href="#results">Results</a></li>
<li><a href="#license">License</a></li>
<li><a href="#refereces">Refereces</a></li>
<li><a href="#contact">Contact</a></li>
</ol>
</details>
<!-- ABOUT THE PROJECT -->
# About The Project
### Welcome to Open-Watch âð»ð a wearable device for health monitoring and fitness tracking.
**Special thanks to [PCBWay](https://www.pcbway.com/) for sponsoring us on this open-source project and providing [these](#pictures) awesome 4-layer PCBs!** Open-Watch is an open-source smartwatch project developed for our B.Sc. final thesis. This smartwatch can measure the linear acceleration of your hand, rotational speed, heart rate, and SpO2 (oxygen saturation). All of these data will be processed by an STM32 processor with an ARM Cortex-M core. You can find these essential components [here](#components).
MPU6050 was used for IMU purposes. We use the Kalman filter to reduce the noise effect and extract clean data from the sensor (3-axis linear acceleration, 3-axis rotational velocity, and 3-axis rotation angle).
MAX30102 is the sensor used for health care purposes. We just read raw data and devolve the processes to the smartphone.
Open-watch will send these collected data to a smartphone via a Bluetooth module. On the smartphone side, an Android app reads the data from Bluetooth and processes them. For health care applications like heart rate and SpO2 analysis, we use ML-based algorithms to extract these parameters from raw data read from the pulse-oximeter sensor. In this section a real-time algorithm for analysis of photoplethysmography signal (PPG) for measurement of SpO2 will be implemented.
The final valuable data will be shown on a smartphone as well as the smartwatch screen.
<div align="center">
<p> <img src="photos/Blocks.png?raw=true "Overview - Front"" width="800"> </p>
</div>
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- DONATION -->
# Donation
Do you want to support us in this project?
<p align="left">
<a href="http://smotlaq.ir/LQgQF">
<img src="https://raw.githubusercontent.com/SMotlaq/LoRa/master/bmc.png" width="200" alt="Buy me a Coffee"/>
</a>
</p>
<p align="right">(<a href="#top">back to top</a>)</p>
# Components
* 4-layer PCB: The PCBs of this project are provided by [PCBWay](https://www.pcbway.com), one of the best PCB factories in the world.
* Main proccessor: [STM32F030C8 (ARM Cortex-M0)](https://www.javanelec.com/Shops/ProductDetail/24347)
* Heartbeat and pulse oximeter sensor: [MAX30102](https://www.aliexpress.com/item/1005001863759524.html?spm=a2g0o.productlist.0.0.6b035ffbNirD5e&algo_pvid=579c2689-3578-4e82-948e-484fa9c52af9&algo_exp_id=579c2689-3578-4e82-948e-484fa9c52af9-0)
* Motion sensor: [MPU6050](http://skytech.ir/product_details.aspx?ID_Parts=2830&MPU6050)
* Display: [1.3" OLED 64*128 pixels](http://skytech.ir/product_details.aspx?ID_Parts=2006&1.3-inch-I2C-OLED-SSD1306-Module)
* Vibration [motor](https://www.javanelec.com/Shops/ProductDetail/38512)
* Bluetooth: [HC-05](https://www.javanelec.com/Shops/ProductDetail/30407)
* Touch driver: [BS814-A](https://micromodern.ir/shop/touch-key-ic/bs814a-1-msop10/)
* Battery: [3.7v Li-Po](https://micmodshop.ir/eshop/battery-products/batteries/battery-lithium-polymer-3-7v-400mah-custom-00/)
* Battery charger: [TP4056](http://skytech.ir/product_details.aspx?ID_Parts=9929&TP4056%20SOP8)
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- ROADMAP -->
# Roadmap
- [x] Hardware design
- [x] Microcontroller
- [x] Vibration motor
- [x] Bluetooth
- [x] Buzzer
- [x] Touch keys
- [x] Charger
- [X] PPG sensor
- [X] MPU6050
- [X] PCB design
- [X] PCB Ordering
- [ ] Body design
- [ ] 3D print
- [x] Soldeing
- [ ] Firmware programming
- [x] RTC
- [x] Bluetooth commands
- [x] Vibration waves
- [x] Buzzer
- [ ] OLED
- [ ] UI/UX
- [x] Touch buttons
- [x] Battery level indicator
- [ ] Power saving
- [ ] MPU6050
- [x] Get raw data
- [ ] Kalman filter
- [ ] Movement detection
- [ ] PPG sensor
- [ ] Get raw data
- [ ] Transfer data using Bluetooth
- [ ] Android programming
- [ ] Get blutooth data
- [ ] UI/UX
- [ ] PPG data analysis
- [ ] Heartbeat
- [ ] SpO2
- [ ] Assembling
- [ ] Final test ð
See the [open issues](https://github.com/SMotlaq/open-watch/issues) for a full list of proposed features (and known issues).
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- PARTS -->
# Pictures
**Overview**
<p> <img src="photos/Pic38.jpg?raw=true "Overview - Front"" width="700"> </p>
<p> <img src="photos/Pic39.jpg?raw=true "Overview - Back"" width="700"> </p>
<!-- ![overview-front](photos/Pic38.jpg?raw=true "Overview - Front")
![overview-back](photos/Pic39.jpg?raw=true "Overview - Back") -->
**PCB - 2D**
<p> <img src="photos/Pic33.jpg?raw=true "2D view of main PCB - both layers"" width="700"> </p>
<!-- ![2D](photos/Pic33.jpg?raw=true "2D view of main PCB - both layers") -->
**PCB - 3D**
<p> <img src="photos/Pic36.jpg?raw=true "3D view of main PCB - front"" width="700"> </p>
<p> <img src="photos/Pic37.jpg?raw=true "3D view of main PCB - back"" width="700"> </p>
<!-- ![3D-front](photos/Pic36.jpg?raw=true "3D view of main PCB - front")
![3D-back](photos/Pic37.jpg?raw=true "3D view of main PCB - back") -->
**PCB - Real**
<p> <img src="photos/Pic40.jpg?raw=true "Real PCB view - front"" width="700"> </p>
<p> <img src="photos/Pic41.jpg?raw=true "Real PCB view - back"" width="700"> </p>
<p> <img src="photos/Pic42.jpg?raw=true "Real PCB view - soldered"" width="700"> </p>
<!-- ![real-front](photos/Pic32.jpg?raw=true "Real PCB view - front")
![real-back](photos/Pic31.jpg?raw=true "Real PCB view - back") -->
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- RESULTS -->
# Results
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- LICENSE -->
# License
Distributed under the MIT License. See `LICENSE.txt` for more information.
<p align="right">(<a href="#top">back to top</a>)</p>
<!-- REFERENCES -->
# Refereces
**Dataset:**
MIMIC-III Database (https://mimic.mit.edu)
[1] *Johnson, A., Pollard, T., & Mark, R. (2016). MIMIC-III Clinical Database (version 1.4). PhysioNet. https://doi.org/10.13026/C2XW26.*
[2] *Moody, B., Moody, G., Villarroel, M., Clifford, G., & Silva, I. (2020). MIMIC-III Waveform Database (version 1.0). PhysioNet. https://doi.org/10.13026/c2607m*
[3] *Kemp, J., Zhang, K., & Dai, A. (2020). MIMIC-III - SequenceExamples for TensorFlow modeling (version1.0.0). PhysioNet. https://doi.org/10.13026/n2v5-5b32.*
**Main references:**
[1] *Kiyasseh et al, CLOCS: Contrastive learning of cardiac signals across space, time, and patients, In Proc. ICML 2021*
[2] *Torres-Soto, J., Ashley, E.A. Multi-task deep learning for cardiac rhythm detection in wearable devices. npj Digit. Med. 3, 116 (2020). https://doi.org/10.1038/s41746-020-00320-4*
[3] *El Hajj C, Kyriacou P.A. Cuffless blood pressure estimation from PPG signals and its derivatives using deep learning models, Biomedical Signal Processing and Control. 70 (2021) https://doi.org/10.1016/j.bspc.2021.102984*
[4] *Solà , J., & Delgado-Gonzalo, R. (2019). The Handbook of Cuffless Blood Pressure Monitoring: A Practical Guide for Clinicians, Researchers, and Engineers. The Handbook of Cuffless Blood Pressure Monito
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基于STM32的手工智能手表源码.zip
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基于STM32的手工智能手表源码.zip (279个子文件)
my_watch_software.uvguix.ASUS 177KB
my_watch_software.axf 440KB
stm32f0xx_hal_i2c.c 214KB
stm32f0xx_hal_tim.c 212KB
stm32f0xx_hal_uart.c 123KB
stm32f0xx_hal_adc.c 92KB
stm32f0xx_hal_tim_ex.c 62KB
stm32f0xx_hal_rtc.c 55KB
stm32f0xx_hal_rcc.c 49KB
stm32f0xx_hal_rtc_ex.c 47KB
stm32f0xx_hal_rcc_ex.c 34KB
stm32f0xx_hal_flash_ex.c 30KB
stm32f0xx_hal_dma.c 27KB
stm32f0xx_hal_flash.c 20KB
stm32f0xx_hal_gpio.c 19KB
stm32f0xx_hal_pwr.c 16KB
stm32f0xx_hal_uart_ex.c 16KB
stm32f0xx_hal.c 15KB
stm32f0xx_hal_exti.c 15KB
stm32f0xx_hal_cortex.c 12KB
stm32f0xx_hal_i2c_ex.c 10KB
system_stm32f0xx.c 10KB
stm32f0xx_hal_pwr_ex.c 8KB
tim.c 7KB
main.c 7KB
stm32f0xx_hal_adc_ex.c 6KB
stm32f0xx_it.c 5KB
usart.c 5KB
adc.c 4KB
i2c.c 3KB
gpio.c 3KB
stm32f0xx_hal_msp.c 2KB
rtc.c 2KB
dma.c 2KB
stm32f0xx_hal_i2c.crf 377KB
stm32f0xx_hal_tim.crf 371KB
stm32f0xx_hal_uart.crf 345KB
main.crf 339KB
stm32f0xx_hal_tim_ex.crf 338KB
stm32f0xx_hal_adc.crf 337KB
stm32f0xx_hal_rcc.crf 336KB
stm32f0xx_hal_rtc.crf 332KB
stm32f0xx_hal_rtc_ex.crf 331KB
stm32f0xx_hal_flash_ex.crf 328KB
stm32f0xx_hal_dma.crf 328KB
stm32f0xx_hal_flash.crf 327KB
stm32f0xx_hal_gpio.crf 326KB
stm32f0xx_hal_exti.crf 326KB
tim.crf 326KB
stm32f0xx_hal_rcc_ex.crf 326KB
usart.crf 325KB
adc.crf 325KB
gpio.crf 325KB
stm32f0xx_hal.crf 325KB
i2c.crf 324KB
stm32f0xx_hal_pwr.crf 324KB
stm32f0xx_hal_i2c_ex.crf 324KB
rtc.crf 324KB
stm32f0xx_it.crf 324KB
stm32f0xx_hal_msp.crf 324KB
stm32f0xx_hal_uart_ex.crf 324KB
dma.crf 324KB
stm32f0xx_hal_adc_ex.crf 324KB
stm32f0xx_hal_cortex.crf 324KB
system_stm32f0xx.crf 323KB
stm32f0xx_hal_pwr_ex.crf 323KB
stm32f0xx_hal_flash_ex.d 3KB
stm32f0xx_hal_uart_ex.d 3KB
main.d 3KB
stm32f0xx_hal_i2c_ex.d 3KB
stm32f0xx_hal_tim_ex.d 3KB
stm32f0xx_hal_rtc_ex.d 3KB
stm32f0xx_hal_adc_ex.d 3KB
stm32f0xx_hal_rcc_ex.d 3KB
stm32f0xx_hal_pwr_ex.d 3KB
stm32f0xx_hal_cortex.d 3KB
stm32f0xx_hal_flash.d 3KB
stm32f0xx_hal_uart.d 3KB
stm32f0xx_hal_gpio.d 3KB
stm32f0xx_hal_exti.d 3KB
stm32f0xx_hal_msp.d 3KB
stm32f0xx_hal_tim.d 3KB
stm32f0xx_hal_pwr.d 3KB
stm32f0xx_hal_dma.d 3KB
stm32f0xx_hal_rcc.d 3KB
stm32f0xx_hal_i2c.d 3KB
stm32f0xx_hal_adc.d 3KB
stm32f0xx_hal_rtc.d 3KB
system_stm32f0xx.d 3KB
stm32f0xx_it.d 3KB
stm32f0xx_hal.d 3KB
usart.d 3KB
gpio.d 3KB
i2c.d 3KB
adc.d 3KB
dma.d 3KB
tim.d 3KB
rtc.d 3KB
startup_stm32f030x8.d 63B
my_watch_software_STM32F030C8Tx.dbgconf 2KB
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