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: "comparison of an open hardware electroencephalography amplifier with medical grade device in brain computer interface applications"
  Abstract: Brain-computer interfaces (BCI) are promising communication devices between humans and machines. BCI based on non-invasive neuroimaging techniques such as electroencephalography (EEG) have many applications , however the dissemination of the technology is limited, in part because of the price of the hardware. In this paper we compare side by side two EEG amplifiers, the consumer grade OpenBCI and the medical grade g.tec g.USBamp. For this purpose, we employed an original montage, based on the simultaneous recording of the same set of electrodes. Two set of recordings were performed. During the first experiment a simple adapter with a direct connection between the amplifiers and the electrodes was used. Then, in a second experiment, we attempted to discard any possible interference that one amplifier could cause to the other by adding "ideal" diodes to the adapter. Both spectral and temporal features were tested -- the former with a workload monitoring task, the latter with an visual P300 speller task. Overall, the results suggest that the OpenBCI board -- or a similar solution based on the Texas Instrument ADS1299 chip -- could be an effective alternative to traditional EEG devices. Even though a medical grade equipment still outperforms the OpenBCI, the latter gives very close EEG readings, resulting in practice in a classification accuracy that may be suitable for popularizing BCI uses.

Connected through hyperedge HE-1 (induced by source paper "implicit analysis of perceptual multimedia experience based on physiological response a review"):
  with members:
    - "perceptual experience analysis for tone mapped hdr videos based on eeg and peripheral physiological signals"

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)