Cece1031

Cece1031's Stars

• subhrockzz/Patient-Health-Monitoring-System

  Working on the model for building Patient Health Monitoring System which measures the Criticality Index of a Person in Ambulance by various parameters like Blood Pressure,Heart Rate,Blood Oxygen Level,Body Temperature and ECG(Person can see the Real Time graph of the parameters).It can automatically ping the Ambulance driver whenever the Patient will critical and Ambulance driver will get the nearby hospital list and Locations. The doctor can see the condition of the Patient from the Hospital also

  Language:Python6

• LOVISHARYX/HRV-and-GSR-as-Viable-Physiological-Markers-for-Mental-Health-Recognition

  Mental stress has become a standard part of day-to-day life. However, experiencing long-term and high-level stress affects the daily life and wellness of the person. Consequently, an individual's performance and management ability degrade significantly in critical situations. Electrocardiogram (ECG), Galvanic Skin Response (GSR), Electromyogram (EMG), Skin Temperature (ST), and Respiration are essential physiological biomarkers to quantify stress effectively. This paper aims to classify the stress level with improved performance based on GSR and ECG-derived Heart Rate Variability (HRV) features using machine and deep learning algorithms. It uses the Stress Recognition in Automobile Drivers (SRAD) dataset, which contains a collection of multiparameter recordings from 17 healthy participants who drive on a prescribed route under various pressure conditions. The work uses Pearson's Correlation, RFECV, and LightGBM feature selection methods with different classifiers to reduce redundancy between features and enhance performance. The accuracy and F1-score for stress level classifications are computed and compared using machine and deep learning algorithms. For binary classification (stress vs. non-stress), Random Forest achieves the best classification accuracy of 93.96 % which is higher than previous works. It also provides an accuracy of 81.41 % for three-class (baseline vs. medium stress vs. high stress) stress level classification.

  Language:Jupyter Notebook112

• cawarr/ECG-Health-Monitor

  Use an ECG signal to derive a heart rate variability and respiration rate model

  Language:Python51

• stereopickle/mental_health_index

  Statistical analysis to identify the key factors that attribute to the progression of depressive symptoms

  Language:Jupyter Notebook41

• MohammedRiazKhan/HealthIndex

  A health information and body mass index calculator which generates workouts and diet recommendations based on the result. As well as providing basic health information.

  Language:Java5

• devprabal/BMI-prediction-of-health-status

  Machine Learning to predict the health status (BMI : Body Mass Index)

  Language:Jupyter Notebook34

• agenthun/BleECG

  基于Material Design设计的蓝牙心率计, 便携穿戴于手腕,追踪自己的心跳健康指数

  Language:Java6726

• lingjuanlv/LSTM-CNN-model-for-HAR

  LSTM-CNN model for Human Activity Recognition

  Language:Python235

• abduallahmohamed/HAR-GCNN

  Code for HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data, IEEE PerCom CoMoRea 2022

  Language:Python137

• zhangzhao156/CNN-for-HAR-on-WISDM-Dataset

  CNN, LSTM, CNN+LSTM for human activity recongnition on WISDM dataset(smartphone dataset)

  Language:Jupyter Notebook198

• microsoft/SGN

  This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”.

  Language:Python18556

• geekfeiw/Multi-Scale-1D-ResNet

  pytorch code of multi scale 1d resnet, we hope it will help your research

  Language:Python21149

• sheikhhanif/ARS

  RNN vs LSTM - Performance comparison on UCI HAR dataset

  Language:Jupyter Notebook75

• ni79ls/har-keras-cnn

  Jupyter Notebook for Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras

  Language:Python15872

• skywateryang/timeseries101

  本教程独立网站已上线

  Language:Jupyter Notebook20959

• hsd1503/resnet1d

  PyTorch implementations of several SOTA backbone deep neural networks (such as ResNet, ResNeXt, RegNet) on one-dimensional (1D) signal/time-series data.

  Language:Python41497

• aqx1991/Motion

  Android端记录跑步计步运动轨迹数据的App

  Language:Java300108

• Aristochi/HappyRun

  这是一款轻量、简易的、采用高德地图SDK记录轨迹和三轴加速度传感器的跑步、计步Android APP应用作业

  Language:Java2813

• jiyouliang/FMap

  宇行地图：高仿高德地图Android客户端（持续更新中...）

  Language:Java408265

• ZhaoYukai/HeartRate

  【Android项目】使用Android手机的摄像头，通过闪光灯识别手指的血管，完成心率的检测，绘制出心率图

  Language:Java25399

• WZMIAOMIAO/deep-learning-for-image-processing

  deep learning for image processing including classification and object-detection etc.

  Language:Python22.6k7.9k

• microsoft/Swin-Transformer

  This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

  Language:Python13.7k2k

• Nuyoah-xlh/CbirByVgg

  CbirByVgg-基于VGG16的图像检索程序，可视化查询并显示，可扩展到自己的图像库。

  Language:Python221

• Nuyoah-xlh/CBIRBySiftAndColor

  使用SIFT特征和颜色特征实现基于内容的图像检索-CBIRBySiftAndColor

  Language:Python8

• changwookjun/nlp-paper

  NLP Paper

  589124

• jsjby/jsjby_2022

  发布23年计算机保研夏令营和预推免通知，往年的保研经验帖；需要带保研或计算机保研资料联系qq：1585601434

  23810

• CS-BAOYAN/CSYuTuiMian2022

  关于2022年CS保研预推免通知公告的汇总，欢迎大家积极分享预推免信息，资瓷一下互联网精神吼不吼啊？

  63061

• tianxiaogua/Twantch

  基于STM32的电子腕表设计。搭载了MPU6050和温湿度传感器，以及一块1.14寸全彩显示屏。

  Language:C16935

• hanghang2333/emotionrecognition

  表情识别

  Language:Python7337

• linw7/Activity-Recognition

  🚀 手机加速度传感器数据进行人体行为识别

  Language:Python6719