Wearable Sensor-Based Human Activity Recognition via Two-Layer Diversity-Enhanced Multiclassifier Recognition Method
نویسندگان
چکیده
منابع مشابه
Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform
Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing...
متن کاملHuman Activity Recognition via Cellphone Sensor Data
The purpose of this project is to identify human activities while using cell phones via mobile sensor data. We collect 2085 data samples, which includes 3-axis acceleration, angular velocity and orientation sensor data, from 4 volunteers using the MATLAB Mobile package. After cleaning, interpolating, and FFT, we get 135 raw features, and we further reduce the feature number to 21 via feature se...
متن کاملHuman Activity Recognition using Wearable Devices Sensor Data
Wearable devices are getting increasingly popular nowadays as the technology products become smaller, more energy efficient and as more sensors are available on our wrist. By wearing these devices everyday, we could easily collect mega-bytes of data each day. In spite of the abundance of available data from these sensors, there isn’t too much information we can tell from these raw data about wh...
متن کاملImproving Fault Tolerance of Wearable Sensor-based Activity Recognition Techniques
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitte...
متن کاملPhysical Human Activity Recognition Using Wearable Sensors
This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-proces...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2019
ISSN: 1424-8220
DOI: 10.3390/s19092039