PrimSeq: a deep learning-based pipeline to quantitate rehabilitation training

1 code implementation • 21 Dec 2021 • Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Audre Wirtanen, Haresh Rajamohan, Kannan Venkataramanan, Dawn Nilsen, Carlos Fernandez-Granda, Heidi Schambra

Here, we present PrimSeq, a pipeline to classify and count functional motions trained in stroke rehabilitation.

Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution

1 code implementation • 3 Nov 2021 • Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda

To address this, we propose a novel approach for high-resolution action identification, inspired by speech-recognition techniques, which is based on a sequence-to-sequence model that directly predicts the sequence of actions.

Action Recognition speech-recognition +2