Where can I find an algorithm for human activity classification using thigh and shank sensors? I am working on a project where I initially need to classify the type of activity a subject is performing based on raw accelerometer and gyroscope data from the thigh and shank of both legs. The type of activities would be day-to-day tasks such as standing, sitting, running, sit-to-stand, stair climbing, if playing sports, cutting, etc.

I have tried reading papers and looking on git to find an algorithm that will do this for me. I know that there are a lot of algorithms available, but none seem to utilize sensors on the leg. Most are sensors on the chest or through a person's phone.

Where would I be able to find an algorithm that will take the data I have an classify the activities being performed? Can I do this with algorithms that aren't initially made for the sensor placement I am using?

Any help would be greatly appreciated.
What you want to do can be called activity recognition or time-series classification. Almost all classification algorithms can be made to do this. A popular choice is to use a type of RNN (recurrent neural network) called a LSTM (long short-term memory). It is made to work with sequences and handles time series quite well. 

Here are some relevant readings that might get you started:

Activity recognition tutorial using RNN models

Similar tutorial using various models