--- tags: - time series - time series classification - monster - HAR license: other pretty_name: WISDM2 size_categories: - 100K. |WISDM2|| |-|-:| |Category|HAR| |Num. Examples|149,034| |Num. Channels|3| |Length|100| |Sampling Freq.|20 Hz| |Num. Classes|6| |License|Other| |Citations|[1]| ***WISDM2*** extends the original *WISDM* dataset by collecting data in real-world environments using the Actitracker system. This system was designed for public use and provides a more extensive collection of sensor readings from users performing the same six activities. The dataset contains 2,980,765 samples with three dimensions, and the data was recorded from a larger and more diverse set of participants in naturalistic settings, offering a valuable resource for real-world activity recognition [1]. The processed dataset has 149,034 time series, each with length 100 (again, representing 5 seconds of data at a sampling rate of 20 Hz). WISDM2 is split based on subjects. [1] Gary Mitchell Weiss and Jeffrey Lockhart. (2012). The impact of personalization on smartphone-based activity recognition. In Workshops at the *26th AAAI Conference on Artificial Intelligence*.