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Record W2092044338 · doi:10.1089/tmj.2006.12.622

A Telemedicine System for Remote Health and Activity Monitoring for the Elderly

2006· article· en· W2092044338 on OpenAlexaff
Polley R. Liu, Max Q.‐H. Meng, Peter Liu, Fanny F.L. Tong, X.J. Chen

Bibliographic record

VenueTelemedicine Journal and e-Health · 2006
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsCarleton University
FundersHong Kong Government
KeywordsTelemedicineTelecareAdaptation (eye)TelehealthComputer scienceHealth careService (business)Business

Abstract

fetched live from OpenAlex

The aging population is placing increasing pressure on healthcare services around the world. Telemedicine, which provides medical information or healthcare services at a distance using telecommunication technologies, is of growing interest to governments and healthcare providers. Existing telemedicine systems are primarily for medical information sharing and consultation with no teleoperation capabilities for activity monitoring. Moreover, the equipment of most systems available to support older patients to stay in their living environment must be tied to a fixed location, which severely limits their feasibility and applicability. In this paper, a new telemedicine structure is introduced for regular and ad hoc health monitoring services. In particular, it aims at scenarios where frequent interactive contacts between patients and professionals are required. This system incorporates several different networking technologies that work harmoniously to facilitate data communication, which potentially have a profound impact on the method of delivering medical service remotely. Another unique characteristic of the developed system is its capabilities of adaptation to network conditions, such as network congestion and availability of bandwidth. The concept of the proposed structure is validated using a laboratory-based test platform with some pilot experiments. Preliminary results demonstrate its feasibility for remote health monitoring services of the elderly. The potential benefits of the system 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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.057
GPT teacher head0.331
Teacher spread0.275 · 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.

Study designOther design
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

Citations20
Published2006
Admission routes1
Has abstractyes

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