Using netmeeting for remote configuration of the Otto Bock C-Leg
Bibliographic record
Abstract
Telehealth has the potential to be a valuable tool for technical and clinical support of computer controlled prosthetic devices. This pilot study examined the use of Internet-based, desktop video conferencing for remote configuration of the Otto Bock C-Leg. Laboratory tests involved connecting two computers running Microsoft NetMeeting over a local area network (IP protocol). Over 56 Kbs(-1), DSL/Cable, and 10 Mbs(-1) LAN speeds, a prosthetist remotely configured a user's C-Leg by using Application Sharing, Live Video, and Live Audio. A similar test between sites in Ottawa and Toronto, Canada was limited by the notebook computer's 28 Kbs(-1) modem. At the 28 Kbs(-1) Internet-connection speed, NetMeeting's application sharing feature was not able to update the remote Sliders window fast enough to display peak toe loads and peak knee angles. These results support the use of NetMeeting as an accessible and cost-effective tool for remote C-Leg configuration, provided that sufficient Internet data transfer speed is available.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".