human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "online group exercises for older adults of different physical abilities"
  Abstract: In this paper we describe the design and validation of a virtual fitness environment aiming at keeping older adults physically and socially active. We target particularly older adults who are socially more isolated, physically less active, and with less chances of training in a gym. The virtual fitness environment, namely Gymcentral, was designed to enable and motivate older adults to follow personalised exercises from home, with a (heterogeneous) group of remote friends and under the remote supervision of a Coach. We take the training activity as an opportunity to create social interactions, by complementing training features with social instruments. Finally, we report on the feasibility and effectiveness of the virtual environment, as well as its effects on the usage and social interactions, from an intervention study in Trento, Italy.

Connected through hyperedge HE-1 (induced by source paper "technologies for promoting social participation in later life"):
  with members:
    - "designing for co located and virtual social interactions in residential care"
    - "agile development for vulnerable populations lessons learned and recommendations"
    - "golden years golden shores a study of elders in online travel communities"
    - "turned 70 it is time to start editing wikipedia"
    - "a location based game for two generations teaching mobile technology to the elderly with the support of young volunteers"
    - "livinglab pjait towards better urban participation of seniors"
    - "senior programmers characteristics of elderly users from stack overflow"

Connected through hyperedge HE-2 (induced by source paper "coachai a conversational agent assisted health coaching platform"):
  with members:
    - "beyond patient monitoring conversational agents role in telemedicine healthcare support for home living elderly individuals"
    - "towards automatic personalised mobile health interventions an interactive machine learning perspective"
    - "domain specific design patterns designing for conversational user interfaces"
    - "a conversational interface to improve medication adherence towards ai support in patient s treatment"
    - "can a chatbot determine my diet addressing challenges of chatbot application for meal recommendation"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.HC(Human-Computer Interaction)