Table 3 Summary of datasets used and data processing methods
From: Multi-sensor fusion based on multiple classifier systems for human activity identification
| Â | Dataset 1 | Dataset 2 |
|---|---|---|
Sensors | Shimmer sensor devices containing 3D accelerometer, 3D gyroscope | Shimmer2 sensor device IMU containing 3D accelerometer, 3D gyroscope, 3D magnetometer and 2-lead electrocardiography (ECG) |
Placement | Right ankle, chest and right wrist | Ankle and wrist |
Physical activities performed | sitting, lying, standing, washing dishes, vacuuming, sweeping, walking, ascending stairs, descending stairs, running, bicycling on the ergometer (50Â w), bicycling on the ergometer (100Â w), rope jumping. | Standing still, sitting and relaxing, lying down, walking, climbing stairs, waist bend forward, the frontal elevation of arms, knee bending(crouching), cycling, jogging, running, jumping |
Number of activities | 13 | 12 |
Number of participants | 19 | 10 |
Sampling rate | 204.8Â Hz | 50Â Hz |
Filtering method | Linear interpolation | Linear interpolation |
Window type and size | 5Â s with 50% overlap | 2Â s |
Feature selection methods | Evolutionary search method, CorrelationAttributeEval, Ranker | Evolutionary search method, CorrelationAttributeEval, Ranker |
Evaluation method | Tenfold cross validation | Tenfold cross validation |