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We used the UP-Fall dataset to conduct this study.
This dataset was collected by Martínez-Villaseñor et al. and made it available to the research community.
They use five wearable sensors to collect accelerometer, gyroscope and ambient light data. In addition, they acquired data from one electroencephalograph (EEG) headset, six infrared sensors, and two cameras.
The pie chart shows the data distribution ratio of the UP-Fall dataset. The number of samples of the five fall activities represented only 9% of the total samples. Six basic daily activities such as Walking (W), Standing (ST), Sitting (SI), Jumping (J), Lying (L) accounted for 90% of the sample. Hence, Up-Fall is both unbalanced datasets that contain very small portion of fall activities.
With unbalanced datasets like UP-Fall, the ability to detect fall activities is a big challenge.
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IEEE/ICACT20220120 Slide.09
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