The proposed framework uses an efficient iterative algorithm to compute initial energy allocations at the beginning of a day.
Movement disorders, such as Parkinson's disease, affect more than 10 million people worldwide.
The typical approach is training a HAR classifier offline with known users and then using the same classifier for new users.
To address this need, system-on-chips (SoC) that are at the heart of these devices provide a variety of control knobs, such as the number of active cores and their voltage/frequency levels.
Recent research on HAR focuses on using smartphones due to their widespread use.