human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "User, device and orientation independent human activity recognition on mobile phones: challenges and a proposal"
  Abstract: Smart phones equipped with a rich set of sensors are explored as alternative platforms for human activity recognition in the ubiquitous computing domain. However, there exist challenges that should be tackled before the successful acceptance of such systems by the masses. In this paper, we particularly focus on the challenges arising from the differences in user behavior and in the hardware. To investigate the impact of these factors on the recognition accuracy, we performed tests with 20 different users focusing on the recognition of basic locomotion activities using the accelerometer, gyroscope and magnetic field sensors. We investigated the effect of feature types, to represent the raw data, and the use of linear acceleration for user, device and orientation-independent activity recognition.

Connected through hyperedge HE-1 (induced by source paper "Similar gait action recognition using an inertial sensor"):
  with members:
    - "Learning multi-level features for sensor-based human action recognition"

Connected through hyperedge HE-2 (induced by source paper "Online pose classification and walking speed estimation using handheld devices"):
  with members:
    - "Regularization Networks and Support Vector Machines"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science