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Record W2069670120 · doi:10.1109/icsens.2013.6688256

Miniaturized low cost wireless data logger for vibration recording of physiological activities

2013· article· en· W2069670120 on OpenAlexaff
Issa Jaafar, Zachary Czarnecki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsAssiniboine Community College
Fundersnot available
KeywordsData loggerAccelerometerUSBWirelessTelemetryTransceiverComputer scienceComputer hardwareAccelerationEmbedded systemReal-time computingSerial communicationTelecommunicationsSoftware

Abstract

fetched live from OpenAlex

This paper presents the development and testing of new Wireless sensor telemetry system designed specifically to be mounted on different parts of the body and record useful motion signals. In this work, a miniaturized USB packaged Wireless data-logger was constructed by a low-power System-on-chip device (CC1111) utilizing 433 MHz ISM transceiver to record body accelerations from multiple sites. The wireless setups reduce the inconvenience for free-moving due to the line connection between sensors and the central data processing recorder. The proposed system is measuring acceleration of range from ±2g to ±16g. To enhance the desired performance, the system is provided with Antenna fault and free-fall detection features. The recorded vibration signals were demonstrated in our experiments, while the subjects performed a series physical moving activities, free-moving, simulated falls and postural changes. In this system, a secure digital MicroSD flash was used to store measured acceleration providing extra data storage.

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.

How this classification was reachedexpand

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.415

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.257
Teacher spread0.213 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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