Dataset
Προβολή σε EDS

Participant Study Data for Cardiovascular Metric Estimation with a Developed PPG Device

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Participant Study Data for Cardiovascular Metric Estimation with a Developed PPG Device
Συγγραφείς: Anneri Appel
Έτος έκδοσης: 2024
Θεματικοί όροι: Medical biotechnology diagnostics (incl. biosensors), Biomedical engineering not elsewhere classified, photoplethismography, biomedical engineering challenges, Biomedical engineering -- Data processing, PPG sensor, optical sensor, wearable technology, Institute for Biomedical Engineering, Department of Mechanical and Mechatronic Engineering
Περιγραφή: With the ongoing advancements of photoplethysmography (PPG) devices for clinical and domestic applications, there exists a distinct lack of publicly available literature addressing the best possible hardware design for these devices. In this project, this question was answered by investigating the hardware design configuration of a PPG device, especially focussing on the light source wavelength, light source brightness, number of light sources, photodetector lens shape, and sensor-to-skin contact pressure. This device was evaluated on the quality of the PPG signals it measures, as well as its ability to accurately estimate the user’s heart rate, blood oxygen saturation, and blood pressure over different skin tones. A participant study was also conducted to collect cardiovascular metric data from 110 participants with varying skin tones, which was used to develop a neural network for blood pressure estimation as well as determine the best hardware configuration of the PPG device. This resulted in the hardware configuration that consisted of a red-and-infrared light-emitting diode (LED) system, a flat lens photodiode, and high sensor-to-skin contact pressure. This configuration was setup with its two red LEDs at a medium level of brightness and four infrared LEDs at a high level of brightness and was primarily used to measure data on the user’s fingertip. The consequent estimations’ mean absolute errors were 3.511 BPM for heart rate, 0.615% for blood oxygen saturation, and 11.279 mmHg for the systolic blood pressure and 6.802 mmHg for the diastolic blood pressure estimations, respectively. Finally, the selected PPG device’s bias to skin tone was determined. It was concluded that the device had very little bias to skin tone, due to it having a 3.817 dB variance over all the skin tones tested. With the successful identification of the most optimal hardware design configuration, future devices are expected to perform with improved accuracy, usability, and versatility in clinical settings. Furthermore, it provides the ...
Τύπος εγγράφου: dataset
Γλώσσα: unknown
Relation: https://figshare.com/articles/dataset/Participant_Study_Data_for_Cardiovascular_Metric_Estimation_with_a_Developed_PPG_Device/27437637
DOI: 10.25413/sun.27437637.v1
Διαθεσιμότητα: https://doi.org/10.25413/sun.27437637.v1
https://figshare.com/articles/dataset/Participant_Study_Data_for_Cardiovascular_Metric_Estimation_with_a_Developed_PPG_Device/27437637
Rights: CC BY 4.0
Αριθμός Καταχώρησης: edsbas.ACAEBA97
Βάση Δεδομένων: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.25413/sun.27437637.v1#
    Name: EDS - BASE (ns324271)
    Category: fullText
    Text: View record from BASE
Header DbId: edsbas
DbLabel: BASE
An: edsbas.ACAEBA97
RelevancyScore: 872
AccessLevel: 3
PubType: Dataset
PubTypeId: unknown
PreciseRelevancyScore: 871.7080078125
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Participant Study Data for Cardiovascular Metric Estimation with a Developed PPG Device
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Anneri+Appel%22">Anneri Appel</searchLink>
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2024
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Medical+biotechnology+diagnostics+%28incl%2E+biosensors%29%22">Medical biotechnology diagnostics (incl. biosensors)</searchLink><br /><searchLink fieldCode="DE" term="%22Biomedical+engineering+not+elsewhere+classified%22">Biomedical engineering not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22photoplethismography%22">photoplethismography</searchLink><br /><searchLink fieldCode="DE" term="%22biomedical+engineering+challenges%22">biomedical engineering challenges</searchLink><br /><searchLink fieldCode="DE" term="%22Biomedical+engineering+--+Data+processing%22">Biomedical engineering -- Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22PPG+sensor%22">PPG sensor</searchLink><br /><searchLink fieldCode="DE" term="%22optical+sensor%22">optical sensor</searchLink><br /><searchLink fieldCode="DE" term="%22wearable+technology%22">wearable technology</searchLink><br /><searchLink fieldCode="DE" term="%22Institute+for+Biomedical+Engineering%22">Institute for Biomedical Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Department+of+Mechanical+and+Mechatronic+Engineering%22">Department of Mechanical and Mechatronic Engineering</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: With the ongoing advancements of photoplethysmography (PPG) devices for clinical and domestic applications, there exists a distinct lack of publicly available literature addressing the best possible hardware design for these devices. In this project, this question was answered by investigating the hardware design configuration of a PPG device, especially focussing on the light source wavelength, light source brightness, number of light sources, photodetector lens shape, and sensor-to-skin contact pressure. This device was evaluated on the quality of the PPG signals it measures, as well as its ability to accurately estimate the user’s heart rate, blood oxygen saturation, and blood pressure over different skin tones. A participant study was also conducted to collect cardiovascular metric data from 110 participants with varying skin tones, which was used to develop a neural network for blood pressure estimation as well as determine the best hardware configuration of the PPG device. This resulted in the hardware configuration that consisted of a red-and-infrared light-emitting diode (LED) system, a flat lens photodiode, and high sensor-to-skin contact pressure. This configuration was setup with its two red LEDs at a medium level of brightness and four infrared LEDs at a high level of brightness and was primarily used to measure data on the user’s fingertip. The consequent estimations’ mean absolute errors were 3.511 BPM for heart rate, 0.615% for blood oxygen saturation, and 11.279 mmHg for the systolic blood pressure and 6.802 mmHg for the diastolic blood pressure estimations, respectively. Finally, the selected PPG device’s bias to skin tone was determined. It was concluded that the device had very little bias to skin tone, due to it having a 3.817 dB variance over all the skin tones tested. With the successful identification of the most optimal hardware design configuration, future devices are expected to perform with improved accuracy, usability, and versatility in clinical settings. Furthermore, it provides the ...
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: dataset
– Name: Language
  Label: Language
  Group: Lang
  Data: unknown
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://figshare.com/articles/dataset/Participant_Study_Data_for_Cardiovascular_Metric_Estimation_with_a_Developed_PPG_Device/27437637
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.25413/sun.27437637.v1
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.25413/sun.27437637.v1<br />https://figshare.com/articles/dataset/Participant_Study_Data_for_Cardiovascular_Metric_Estimation_with_a_Developed_PPG_Device/27437637
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: CC BY 4.0
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.ACAEBA97
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.ACAEBA97
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.25413/sun.27437637.v1
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Medical biotechnology diagnostics (incl. biosensors)
        Type: general
      – SubjectFull: Biomedical engineering not elsewhere classified
        Type: general
      – SubjectFull: photoplethismography
        Type: general
      – SubjectFull: biomedical engineering challenges
        Type: general
      – SubjectFull: Biomedical engineering -- Data processing
        Type: general
      – SubjectFull: PPG sensor
        Type: general
      – SubjectFull: optical sensor
        Type: general
      – SubjectFull: wearable technology
        Type: general
      – SubjectFull: Institute for Biomedical Engineering
        Type: general
      – SubjectFull: Department of Mechanical and Mechatronic Engineering
        Type: general
    Titles:
      – TitleFull: Participant Study Data for Cardiovascular Metric Estimation with a Developed PPG Device
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Anneri Appel
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1