Update README.md

README.md

@@ -22,6 +22,6 @@ Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
 |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]. Both WISDM and WISDM2 are split based on subjects.
+***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 *26<sup>th</sup> AAAI Conference on Artificial Intelligence*.