Evidence map›Paper›PMID 38264154›Full record

ArticleACM transactions on embedded computing systems : TECS2023

BASS: Safe Deep Tissue Optical Sensing for Wearable Embedded Systems.

Kourosh Vali, Ata Vafi, Begum Kasap, Soheil Ghiasi

Abstract read
In one paragraph

Article in ACM transactions on embedded computing systems : TECS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. JOIN: Optimized Light Source Activation for Deep Tissue Optical Sensing.... ACM/IEEE International Conference on Cyber-Physical Systems. IEEE/ACM International Conference on Cyber-Physical Systems · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kourosh ValiUniversity of California, Davis, Electrical and Computer Engineering Department, USA.ORCID 0000-0002-7165-6715
Ata VafiUniversity of California, Davis, Electrical and Computer Engineering Department, USA.ORCID 0000-0002-4540-1129
Begum KasapUniversity of California, Davis, Electrical and Computer Engineering Department, USA.ORCID 0000-0001-5894-2883
Soheil GhiasiUniversity of California, Davis, Electrical and Computer Engineering Department, USA.ORCID 0000-0002-1036-791X

Funding

TRD3: Data Analytics and Intelligent Systems (AI-ML-DL-Visualization)P41EB032840 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Griffith R. Harsh · 2022 to 2026
$6.7M
Validation of Transabdominal Fetal Pulse Oximetry in Hypoxic Fetal Lamb ModelsR21HD097467 · NICHD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FARMER, DIANA LEE, GHIASI, SOHEIL · 2020 to 2021
$413k
NIBIB NIH HHS P41 EB032840NICHD NIH HHS R21 HD097467
6 · The paper itself

Abstract

In wearable optical sensing applications whose target tissue is not superficial, such as deep tissue oximetry, the task of embedded system design has to strike a balance between two competing factors. On one hand, the sensing task is assisted by increasing the radiated energy into the body, which in turn, improves the signal-to-noise ratio (SNR) of the deep tissue at the sensor. On the other hand, patient safety consideration imposes a constraint on the amount of radiated energy into the body. In this paper, we study the trade-offs between the two factors by exploring the design space of the light source activation pulse. Furthermore, we propose BASS, an algorithm that leverages the activation pulse design space exploration, which further optimizes deep tissue SNR via spectral averaging, while ensuring the radiated energy into the body meets a safe upper bound. The effectiveness of the proposed technique is demonstrated via analytical derivations, simulations, and

Indexed as

deep tissue optical sensingdesign space explorationinternet of medical thingsmedical cyber-physical systemsmulti-objective optimizationwearable embedded systems

Identifiers

PMID38264154
PMCPMC10805365

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.