{"id":13586435,"url":"https://github.com/chizhanyuefeng/Realtime-Fall-Detection-for-RNN","last_synced_at":"2025-04-07T15:32:00.525Z","repository":{"id":107654743,"uuid":"137432027","full_name":"chizhanyuefeng/Realtime-Fall-Detection-for-RNN","owner":"chizhanyuefeng","description":"Real-time  ADLs and Fall Detection implement 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and Baselines"],"readme":"# Real-time Fall Detection for RNN(AFD-RNN)\n\n\u003cp align=\"left\"\u003e\n\u003cimg src=\"https://github.com/chizhanyuefeng/Fall_Detection_for_RNN/blob/master/result/rnn.gif\", width=\"720\"\u003e\n\u003c/p\u003e\n\nresult picture illustrate：\n\n- The red,green,blue lines is acceleration sensor's x,y,z data。\n- In the picture ,\"correct\" is the ground truth,\"predict\" is AFD-RNN network predict data\n- Fall1、Fall2、Fall3 and Fall4 are represent Forward-lying,Front-knees-lying,Back-sitting-chair,Sideward-lying \n\n## AFD-RNN using RNN \nThe sensors(acceleration and gyroscope sensor) is realtime to collect data,so we using rnn to detect the people movement.\n\n## Requirenment\n- TensorFlow \u003e= 1.4\n- python3\n- matplotlib\n\n## Class\nSitting,standing,stand to sit,sit to stand,upstairs,downstairs,lying,jumping,joging,walking and fall.\n\n## Train and test\n\n### 1.Train data\n- The data collect frequence is 50Hz\n- Need acceleration and gyroscope sensor\n\n### 2.Before training\nPut the train data to ./dataset/train/,and use kalman filter  to handle the data.\n\n\n    python utils.py\n\n### 3.Training\n    \n    python train_rnn.py\n    \n## 4.Testing\nPut the test data to ./dataset/test/,and use kalman filter  to handle the data.\n\n\n    python run_rnn.py\n    \n## Dataset\n\nWe using public dataset [MobileFall](http://www.bmi.teicrete.gr/index.php/research/mobiact) to train and test our net.\n\nI upload the dataset at [Baidu网盘](https://pan.baidu.com/s/1arZMNPs1GzWrQf4beJFCSQ),if you cant download from [MobileFall](http://www.bmi.teicrete.gr/index.php/research/mobiact),you can try this\n\nThe final accuracy is 98.78%\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchizhanyuefeng%2FRealtime-Fall-Detection-for-RNN","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchizhanyuefeng%2FRealtime-Fall-Detection-for-RNN","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchizhanyuefeng%2FRealtime-Fall-Detection-for-RNN/lists"}