SpO<sub>2</sub> Measurement: Non-Idealities and Ways to Improve Estimation Accuracy in Wearable Pulse Oximeters

Berwal, Deepak; Kuruba, Ajay; Shaikh, Aatha Mohin; Udupa, Anand; Baghini, Maryam Shojaei

doi:10.1109/jsen.2022.3170069

Cited by 14 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Artifacts can be effectively removed from EEG sensors using graph signal processing [31]. Motion artifacts can be reduced using analytical software tools [32], enhanced peak and valley detection algorithms [33], or through Fourier transformation [34].…”

Section: Accuracy Improvement In Body Sensorsmentioning

confidence: 99%

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

Sarkar,

Lee,

Sahoo

2024

Electronics

View full text Add to dashboard Cite

Ambient Intelligence (AMI) represents a significant advancement in information technology that is perceptive, adaptable, and finely attuned to human needs. It holds immense promise across diverse domains, with particular relevance to healthcare. The integration of Artificial Intelligence (AI) with the Internet of Medical Things (IoMT) to create an AMI environment in medical contexts further enriches this concept within healthcare. This survey provides invaluable insights for both researchers and practitioners in the healthcare sector by reviewing the incorporation of AMI techniques in the IoMT. This analysis encompasses essential infrastructure, including smart environments and spectrum for both wearable and non-wearable medical devices to realize the AMI vision in healthcare settings. Furthermore, this survey provides a comprehensive overview of cutting-edge AI methodologies employed in crafting IoMT systems tailored for healthcare applications and sheds light on existing research issues, with the aim of guiding and inspiring further advancements in this dynamic field.

show abstract

Section: Accuracy Improvement In Body Sensorsmentioning

confidence: 99%

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

Sarkar,

Lee,

Sahoo

2024

Electronics

View full text Add to dashboard Cite

show abstract

“…There are early possibilities, such as green light oximetry, cameras, and improved algorithms. [6][7][8] However, "simple replacement" may neither be simple, cheap, nor timely. The objective of this manuscript is to describe the financial and logistical burden in replacing pulse oximeters at one health system and across the United States.…”

Section: Introductionmentioning

confidence: 99%

The High Price of Equity in Pulse Oximetry: A cost evaluation and need for interim solutions

Dempsey,

Lindsay,

Tcheng

et al. 2023

Preprint

View full text Add to dashboard Cite

Importance: Disparities in pulse oximetry accuracy, disproportionately affecting patients of color, have been associated with serious clinical outcomes. Although many have called for pulse oximetry hardware replacement, the cost associated with this replacement is not known. Objective: To estimate the cost of replacing all pulse oximetry hardware throughout a hospital system. Design: Single-center survey, 2023 Setting: Single center. Participants: One academic medical center with three hospitals. Main Outcomes and Measures: Cost of fleet replacement as identified by current day prices for hardware. Results: New and used prices for 5,079/5,678 (89.5%) across three hospitals for pulse oximetry devices were found. The average equipment cost to replace pulse oximetry hardware is $15,704.12 per bed. Replacement and integration costs are estimated at $28.5-31.8 million for the entire medical system. Extrapolating these costs to 5,564 hospitals in the United States results in an estimated cost of $14.1 billion. Conclusions and Relevance: “Simply replacing” pulse oximetry hardware to address disparities may be neither simple, cheap, or timely. Solutions for addressing pulse oximetry accuracy disparities leveraging current technology may be necessary.

show abstract

PPG heart rate extraction algorithm based on the motion artifact intensity Classification and removal framework

Hao,

Wang,

Zhang

et al. 2024

Biomedical Signal Processing and Control

View full text Add to dashboard Cite

SpO₂ Measurement: Non-Idealities and Ways to Improve Estimation Accuracy in Wearable Pulse Oximeters

Cited by 14 publications

References 30 publications

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

The High Price of Equity in Pulse Oximetry: A cost evaluation and need for interim solutions

PPG heart rate extraction algorithm based on the motion artifact intensity Classification and removal framework

Contact Info

Product

Resources

About

SpO2 Measurement: Non-Idealities and Ways to Improve Estimation Accuracy in Wearable Pulse Oximeters

Cited by 14 publications

References 30 publications

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

Smart Healthcare: Exploring the Internet of Medical Things with Ambient Intelligence

The High Price of Equity in Pulse Oximetry: A cost evaluation and need for interim solutions

PPG heart rate extraction algorithm based on the motion artifact intensity Classification and removal framework

Contact Info

Product

Resources

About

SpO₂ Measurement: Non-Idealities and Ways to Improve Estimation Accuracy in Wearable Pulse Oximeters