Ultra wideband for wireless real-time monitoring of neural signals.
Performance of an ultra wideband (UWB) wireless system for real-time neural signal monitoring is evaluated by comparing spiking characteristics between transmitted and received signals for different experimental set-ups. Spike detection quality is selected as the main spiking characteristic of evalu...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 47; no. 6; pp. 649 - 655 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105531513&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105531513 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jun2009 vid: 47 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105531513 NLM19340472 2010281059 10.1007/s11517-009-0480-x NLM19340472 105531513 ppf: 649 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Ultra wideband for wireless real-time monitoring of neural signals. aug: au: Tarín C Traver L Martí P Cardona N Tarín, Cristina Traver, Lara Martí, Paula Cardona, Narcís affil: Institute for Telecommunications and Multimedia Applications, Technical University of Valencia, Spain sug: subj: Cerebellum Physiology Monitoring, Physiologic Methods Telemetry Methods Action Potentials Physiology Animals Rats Signal Processing, Computer Assisted ab: Performance of an ultra wideband (UWB) wireless system for real-time neural signal monitoring is evaluated by comparing spiking characteristics between transmitted and received signals for different experimental set-ups. Spike detection quality is selected as the main spiking characteristic of evaluated signals. Results are presented in receiver-operating characteristics and area-under-the-curve (AUC). In order to assess spike detection quality, a set of artificially generated neural signals is constructed from real neural recordings such that the ground truth is known. Data analysis shows how channel signal-to-noise-ratio (SNR) variation affects AUC in different signal SNR cases. Signals with low SNRs get less affected by reduced channel SNRs than those with higher SNR. Increasing bit error rate modifies spiking characteristics such that an under-estimation of the spiking frequency occurs due to spike losses. For practical application of real-time neural signal monitoring, UWB seems to offer best transmission conditions in a near-body environment. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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