Myoelectric control researcher (U. Saskatchewan) on calibration-efficient surface-EMG decoding and amputee transfer
2
papers here
0
reviewed by Evolve
2
first-author
0
corresponding
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works · OpenAlex
6
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-09-28) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
Not yet scored: a validated output measure is unavailable for this record. Once coverage is confirmed, the axis would quantify total publication volume, venue types and year-over-year growth beyond the raw yearly counts already visible.
Impact—
Not yet scored: citation coverage is too thin for a comparable impact measure. The axis would capture citation-based influence — total citations, citing works and field-normalised standing — once the bibliographic record matures.
Focus—
Not yet scored despite visible topic labels (EMG studies, sensor and energy-harvesting materials, EEG/BCI, neural engineering). The axis would measure topical concentration versus spread across all outputs; reliable scoring needs fuller, disambiguated records.
Collaboration14/100
Score 14 reflects a near-solo working pattern: the OpenAlex snapshot lists just one distinct coauthor, and both catalogued 2026 papers are first-authored (non-corresponding) studies, with W. J. Zhang the recurring frequent collaborator. For an early-career record this is common, but it limits cross-institution reach; growth would likely come from multi-site EMG data collection and co-supervised amputee studies with clinical partners.
Activity86/100
Score 86 is backed by clear acceleration: OpenAlex yearly counts rise from 4 works (2023) and 2 (2024) to 7 (2025) and 9 (2026), with 18 works in the last three years against an h-index of 6 and an i10-index of 2. The 2026 peak coincides with two first-author arXiv studies on calibration-budget personalisation and intact-to-amputee EMG transfer.
Reproducibility—
Not yet scored at profile level. The axis would measure code and data release, protocol detail and artefact availability; so far the two reviewed papers carry only a medium repro-readiness flag, and one explicitly lacks released code.
Research summary
Jethro Odeyemi is an early-career researcher at the University of Saskatchewan (Canada) working at the intersection of surface electromyography, machine learning and neural engineering. The Evolve-catalogued record centres on a single organising question: how much calibration data does myoelectric gesture decoding actually need? Two 2026 first-author arXiv studies attack it from complementary sides. One personalises a cross-user sEMG encoder on NinaPro, showing full fine-tuning wins at every calibration budget while gradient-free prototypical adaptation recovers 52–78% of its gain at near-zero cost. The other examines intact-to-amputee transfer from DB2 to DB3, finding intact-subject pretraining beats scarce amputee data once calibrated, while candidly flagging n=11, a pool-size confound, and no released code. Bibliometric context (OpenAlex): h-index 6, i10-index 2, and 18 works in the last three years, with annual counts rising from 4 (2023) and 2 (2024) to 7 (2025) and 9 (2026) — an activity dimension of 86/100. Topic clusters span muscle activation and EMG studies, advanced sensor and energy-harvesting materials, EEG/brain-computer interfaces, neural engineering and neural-network applications. The collaboration footprint is narrow (one distinct coauthor; W. J. Zhang recurring), scoring 14/100. Overall this is a fast-moving, focused early-stage profile whose impact and reproducibility axes remain unscored pending fuller data.
Collaboration pattern
The record shows a near-solo pattern: OpenAlex lists only one distinct coauthor, and W. J. Zhang is the recurring frequent collaborator; the collaboration dimension scores 14/100. Both catalogued 2026 papers are first-authored but non-corresponding, consistent with supervised early-career work. No multi-institution or clinical co-authorship appears yet, so partnership breadth cannot be assessed beyond this small footprint.
Research keywords
Highlights
Full fine-tuning wins every calibration budget on NinaPro
Intact pretraining plus small calibration beats scarce amputee data
Calibration budget as the unifying research question
Timeline
- 2023First year in the OpenAlex record, with 4 works published.
- 2024Quietest recorded year, with only 2 works.
- 2025Output rebounded to 7 works, more than triple the 2024 count.
- 2026Most productive year: 9 works; two first-author arXiv studies on calibration-budget personalisation and intact-to-amputee sEMG transfer entered the Evolve catalog.
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- Bibliometrics come from OpenAlex only (identity source: openalex); coverage and name disambiguation may be incomplete for an early-career record.
- Output, impact, focus and reproducibility dimensions are unscored because the underlying data is insufficient; h-index 6 and i10-index 2 are shown raw, without field normalisation.
- Only two papers have been reviewed in the Evolve catalog; the remaining works behind the yearly counts are not individually assessed.
- The profile is name-resolved from public bibliographic data tied to ORCID 0009-0001-5170-9357.