/FD-CNN

ADL and Fall Detection

Primary LanguagePython

AFD-CNN(ADL and Fall Detection Convolutional Neural Networks)

our paper[https://ieeexplore.ieee.org/document/8662651]

Sensor data to img

if the 3-axes of the human motion model are considered as the 3 channels of a RGB image, the value of the XYZ axial data can be mapped into the value of the RGB channel data in a RGB image respectively. Namely, each 3-axial data can be converted into an RGB pixel. The 400 pieces of 3-axial data cached in the sliding window can be viewed as a bitmap with size of 20 or 20 pixels.

you can use .utils.transform.data2image func to make sensor data to img

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ADLs and fall data graph

image_3 image_4 image_5 image_5

sensor data to img

image_7

Net construct

we use imgs to train our network

image_1

Net performance

  • accuracy = 0.978718
Class Sensitivity Specificity
Fall 1.000000 0.998654
Walk 0.969072 1.000000
Jog 0.983051 0.993243
Jump 0.948980 0.998684
up stair 0.989474 0.997379
down stair 0.967213 0.991848
stand to sit 0.981481 0.998667
sit to stand 0.990476 0.997344
Average 0.978718 0.996977

Requirenments

  • python3
  • tensorflow 1.4.0
  • pandas
  • numpy
  • matplotlib

How to train and test

python ./src/cnn.py

Dataset

we need two public datasets.