# Submissions for: Human Motion Recognition Using IMUs

|#| Submission | Links |
|-|-|-------------------------------------------|
|1|[Edge-Optimized HAR Pipeline with Logistic Regression and MATLAB Mobile Integration](https://github.com/bcap52/EdgeHAR-Efficient-Human-Activity-Recognition-Using-IMU-Sensors)<br/> Implements an edge-deployable human activity recognition system using logistic regression on windowed IMU features from the HARTH dataset, achieving 93% test accuracy with MATLAB Mobile validation. <br><br> **Authors:** Muhammed Abdulrehman Bin Yasin <br/> **Affiliation:** Bahria University <br> **Submission Date:** 2026-07-13|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/bcap52/EdgeHAR-Efficient-Human-Activity-Recognition-Using-IMU-Sensors) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=bcap52/EdgeHAR-Efficient-Human-Activity-Recognition-Using-IMU-Sensors) <br>  <br><br><br> [![Trend: Artificial Intelligence](https://img.shields.io/badge/Trend-Artificial%20Intelligence-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md)|
|2|[1D-CNN Human Activity Recognition from Raw Smartphone IMU Signals](https://github.com/BHOGALA-SRIKA/ActivityRecognition-1DCNN)<br/> Implements a 1D Convolutional Neural Network in MATLAB to classify six human activities from 9-channel raw IMU sensor data, achieving 91.92% accuracy on the UCI HAR dataset. <br><br> **Authors:** BHOGALA SRIKA, Bhogala Srika <br/> **Affiliation:** PES University <br> **Submission Date:** 2026-07-12|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/BHOGALA-SRIKA/ActivityRecognition-1DCNN) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=BHOGALA-SRIKA/ActivityRecognition-1DCNN) <br>  <br><br><br> [![Trend: Artificial Intelligence](https://img.shields.io/badge/Trend-Artificial%20Intelligence-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md)|
|3|[MATLAB Mobile Fitness Tracker: Activity and Diet Analysis](https://github.com/Justin-pyth/matlab-mobile-fitness-tracker)<br/> A MATLAB app tracking fitness activities (classified via IMU/GPS and ML models) and food intake (Nutritionix API), providing workout analysis, intensity scores, and dietary management for personalized fitness goals. <br><br> **Authors:** Kevin Le, Justin Wu, Tenzin Choezin <br/> **Affiliation:** University of California, Davis, and University of California, Irvine <br> **Submission Date:** 2025-08-27|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/Justin-pyth/matlab-mobile-fitness-tracker) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=Justin-pyth/matlab-mobile-fitness-tracker) <br>  <br><br><br> [![Trend: Artificial Intelligence](https://img.shields.io/badge/Trend-Artificial%20Intelligence-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md)|
|4|[IMU-Based Human Motion Recognition for Running Detection](https://github.com/StavrosKeda/Human-running-Recognition-Using-AI.git)<br/> This project classifies human running motion using smartphone IMU data, processed into spectrograms and fed to a GoogLeNet model for real-time running/not-running detection via MATLAB Mobile. <br><br> **Authors:** Stavros Kedaritis <br/> **Affiliation:** University of Cyprus <br> **Submission Date:** 2024-02-05|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/StavrosKeda/Human-running-Recognition-Using-AI.git) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=StavrosKeda/Human-running-Recognition-Using-AI) <br>  <br><br><br> [![Trend: Artificial Intelligence](https://img.shields.io/badge/Trend-Artificial%20Intelligence-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Artificial%20Intelligence.md)|