Taking Control: A Novel Galvanic Stimulation Device for the Visually Impaired.
Bibliographic record
Abstract
The white cane has been the prominent and widely used mobility aid by visually impaired persons for many years, however, there are some limitations associated with the white cane mobility aid device. Primarily, the white cane exhibits restricted capability in detecting ground-level obstacles in proximity and does not provide reliable detection of aerial obstacles. Our work proposes a device for the safe navigation of visually impaired persons utilizing a non-invasive galvanic vestibular stimulation (GVS) technique. By delivering a signal (1-1.2mA) delivered behind the ear via electrode pads to the vestibular system, we induce a sensation of steering thereby facilitating navigation. Our proposed device utilizes a combination of Intel’s D435 depth camera and an object detection model, YOLOv5, to identify and process the detection of obstacles within a 3-meter range. Within 0.2 seconds, the object is detected, and the algorithm assesses the situation and sends instructions via User Datagram Protocol (UDP) packets wirelessly to the GVS device. The device receives the packets and steers the subject (human) autonomously. In total, four tests with different scenarios have been conducted, through experimentation, it was found that the system could successfully detect, process, and transmit geospatial information to the GVS module; and steers the user into the correct trajectory to avoid any hazards obstructing the user’s path.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".