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Record W2126568521 · doi:10.1109/tbcas.2010.2052616

Mechanically Flexible Wireless Multisensor Platform for Human Physical Activity and Vitals Monitoring

2010· article· en· W2126568521 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Biomedical Circuits and Systems · 2010
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSensor nodeWearable computerWireless sensor networkComputer scienceFirmwareData acquisitionWirelessNode (physics)Real-time computingComputer hardwareKey distribution in wireless sensor networksEmbedded systemWireless networkEngineering

Abstract

fetched live from OpenAlex

Practical usability of the majority of current wearable body sensor systems for multiple parameter physiological signal acquisition is limited by the multiple physical connections between sensors and the data-acquisition modules. In order to improve the user comfort and enable the use of these types of systems on active mobile subjects, we propose a wireless body sensor system that incorporates multiple sensors on a single node. This multisensor node includes signal acquisition, processing, and wireless data transmission fitted on multiple layers of a thin flexible substrate with a very small footprint. Considerations for design include size, form factor, reliable body attachment, good signal coupling, low power consumption, and user convenience. The prototype device measures 55 15 mm and is 3 mm thick. The unit is attached to the patient's chest, and is capable of performing simultaneous measurements of parameters, such as body motion, activity intensity, tilt, respiration, cardiac vibration, cardiac potential (ECG), heart rate, and body surface temperature. In this paper, we discuss the architecture of this system, including the multisensor hardware, the firmware, a mobile-phone receiver unit, and assembly of the first proof-of-concept prototype. Preliminary performance results on key elements of the system, such as power consumption, wireless range, algorithm efficiency, ECG signal quality for heart-rate calculations, as well as synchronous ECG and body activity signals are also presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.267
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it