Implementation of Vital Signs Detection Algorithm for Supervising the Evacuation of Individuals with Special Needs Article Swipe
Krzysztof Konopko
,
Dariusz Janczak
,
Wojciech Walendziuk
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25237391
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25237391
The article describes a system for monitoring the vital parameters of evacuated individuals, integrating three key functionalities: pulse detection, verification of wristband contact with the skin, and motion recognition. For pulse detection, the system employs the MAX30102 optical sensor and a signal processing algorithm presented in the study. The algorithm is based on spectral analysis using the Fast Fourier Transform (FFT) and incorporates a nonparametric estimator of the probability density function (PDF) in the form of Kernel Density Estimation (KDE). This developed real-time algorithm enables reliable assessment of vital parameters of evacuated individuals. The wristband contact with the skin is verified by measuring the brightness of backscattered light and the temperature of the wrist. Motion detection is achieved using the MPU-9250 inertial module, which analyzes acceleration across three axes. This allows the system to distinguish between states of rest and physical activity, which is crucial for accurately interpreting vital parameters during evacuation. The experimental studies, which were performed on a representative group of individuals, confirmed the correctness of the developed algorithm. The system ensures reliable monitoring of vital parameters by combining precise pulse detection, skin contact verification, and motion analysis. The classifier achieves nearly 95% accuracy and an F1-score of 0.9465, which indicates its high quality. This level of effectiveness can be considered fully satisfactory for evacuation monitoring systems.
Related Topics
Concepts
Algorithm
Computer science
Correctness
Estimator
Vital signs
Kernel density estimation
Remote patient monitoring
Computer vision
Acceleration
Waveform
Artificial intelligence
Signal processing
Classifier (UML)
Interfacing
Kernel (algebra)
Motion detection
Real-time computing
SIGNAL (programming language)
Key (lock)
Pulse (music)
Simulation
Brightness
Nonparametric statistics
Engineering
Inertial measurement unit
Fourier transform
Probability density function
Histogram
Statistical classification
Motion control
Control system
Accelerometer
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25237391
- https://www.mdpi.com/1424-8220/25/23/7391/pdf
- OA Status
- gold
- OpenAlex ID
- https://openalex.org/W7108754745
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W7108754745Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s25237391Digital Object Identifier
- Title
-
Implementation of Vital Signs Detection Algorithm for Supervising the Evacuation of Individuals with Special NeedsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-04Full publication date if available
- Authors
-
Krzysztof Konopko, Dariusz Janczak, Wojciech WalendziukList of authors in order
- Landing page
-
https://doi.org/10.3390/s25237391Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/25/23/7391/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/25/23/7391/pdfDirect OA link when available
- Concepts
-
Algorithm, Computer science, Correctness, Estimator, Vital signs, Kernel density estimation, Remote patient monitoring, Computer vision, Acceleration, Waveform, Artificial intelligence, Signal processing, Classifier (UML), Interfacing, Kernel (algebra), Motion detection, Real-time computing, SIGNAL (programming language), Key (lock), Pulse (music), Simulation, Brightness, Nonparametric statistics, Engineering, Inertial measurement unit, Fourier transform, Probability density function, Histogram, Statistical classification, Motion control, Control system, AccelerometerTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
Full payload
| id | https://openalex.org/W7108754745 |
|---|---|
| doi | https://doi.org/10.3390/s25237391 |
| ids.doi | https://doi.org/10.3390/s25237391 |
| ids.openalex | https://openalex.org/W7108754745 |
| fwci | 0.0 |
| type | article |
| title | Implementation of Vital Signs Detection Algorithm for Supervising the Evacuation of Individuals with Special Needs |
| biblio.issue | 23 |
| biblio.volume | 25 |
| biblio.last_page | 7391 |
| biblio.first_page | 7391 |
| topics[0].id | https://openalex.org/T11196 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.28277474641799927 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2204 |
| topics[0].subfield.display_name | Biomedical Engineering |
| topics[0].display_name | Non-Invasive Vital Sign Monitoring |
| topics[1].id | https://openalex.org/T10914 |
| topics[1].field.id | https://openalex.org/fields/28 |
| topics[1].field.display_name | Neuroscience |
| topics[1].score | 0.04478521645069122 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2805 |
| topics[1].subfield.display_name | Cognitive Neuroscience |
| topics[1].display_name | Tactile and Sensory Interactions |
| topics[2].id | https://openalex.org/T10645 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.02691081538796425 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2711 |
| topics[2].subfield.display_name | Emergency Medicine |
| topics[2].display_name | Cardiac Arrest and Resuscitation |
| is_xpac | False |
| apc_list.value | 2400 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2598 |
| apc_paid.value | 2400 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2598 |
| concepts[0].id | https://openalex.org/C11413529 |
| concepts[0].level | 1 |
| concepts[0].score | 0.5940771102905273 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[0].display_name | Algorithm |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.5888860821723938 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C55439883 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5834865570068359 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q360812 |
| concepts[2].display_name | Correctness |
| concepts[3].id | https://openalex.org/C185429906 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5210973024368286 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1130160 |
| concepts[3].display_name | Estimator |
| concepts[4].id | https://openalex.org/C2776890885 |
| concepts[4].level | 2 |
| concepts[4].score | 0.48369747400283813 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1067560 |
| concepts[4].display_name | Vital signs |
| concepts[5].id | https://openalex.org/C71134354 |
| concepts[5].level | 3 |
| concepts[5].score | 0.43586957454681396 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q458825 |
| concepts[5].display_name | Kernel density estimation |
| concepts[6].id | https://openalex.org/C175079658 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4062146544456482 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q7312165 |
| concepts[6].display_name | Remote patient monitoring |
| concepts[7].id | https://openalex.org/C31972630 |
| concepts[7].level | 1 |
| concepts[7].score | 0.39622732996940613 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[7].display_name | Computer vision |
| concepts[8].id | https://openalex.org/C117896860 |
| concepts[8].level | 2 |
| concepts[8].score | 0.3862236738204956 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11376 |
| concepts[8].display_name | Acceleration |
| concepts[9].id | https://openalex.org/C197424946 |
| concepts[9].level | 3 |
| concepts[9].score | 0.3711758255958557 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1165717 |
| concepts[9].display_name | Waveform |
| concepts[10].id | https://openalex.org/C154945302 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3593152165412903 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[10].display_name | Artificial intelligence |
| concepts[11].id | https://openalex.org/C104267543 |
| concepts[11].level | 3 |
| concepts[11].score | 0.3531641364097595 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q208163 |
| concepts[11].display_name | Signal processing |
| concepts[12].id | https://openalex.org/C95623464 |
| concepts[12].level | 2 |
| concepts[12].score | 0.35018572211265564 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q1096149 |
| concepts[12].display_name | Classifier (UML) |
| concepts[13].id | https://openalex.org/C2776303644 |
| concepts[13].level | 2 |
| concepts[13].score | 0.3499841094017029 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1020499 |
| concepts[13].display_name | Interfacing |
| concepts[14].id | https://openalex.org/C74193536 |
| concepts[14].level | 2 |
| concepts[14].score | 0.3431166708469391 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q574844 |
| concepts[14].display_name | Kernel (algebra) |
| concepts[15].id | https://openalex.org/C2780624872 |
| concepts[15].level | 3 |
| concepts[15].score | 0.32535600662231445 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q852453 |
| concepts[15].display_name | Motion detection |
| concepts[16].id | https://openalex.org/C79403827 |
| concepts[16].level | 1 |
| concepts[16].score | 0.3218381106853485 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q3988 |
| concepts[16].display_name | Real-time computing |
| concepts[17].id | https://openalex.org/C2779843651 |
| concepts[17].level | 2 |
| concepts[17].score | 0.31830471754074097 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7390335 |
| concepts[17].display_name | SIGNAL (programming language) |
| concepts[18].id | https://openalex.org/C26517878 |
| concepts[18].level | 2 |
| concepts[18].score | 0.3151649236679077 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q228039 |
| concepts[18].display_name | Key (lock) |
| concepts[19].id | https://openalex.org/C2780167933 |
| concepts[19].level | 3 |
| concepts[19].score | 0.3039781451225281 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q1550652 |
| concepts[19].display_name | Pulse (music) |
| concepts[20].id | https://openalex.org/C44154836 |
| concepts[20].level | 1 |
| concepts[20].score | 0.3033711314201355 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q45045 |
| concepts[20].display_name | Simulation |
| concepts[21].id | https://openalex.org/C125245961 |
| concepts[21].level | 2 |
| concepts[21].score | 0.29117551445961 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q221656 |
| concepts[21].display_name | Brightness |
| concepts[22].id | https://openalex.org/C102366305 |
| concepts[22].level | 2 |
| concepts[22].score | 0.29099011421203613 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q1097688 |
| concepts[22].display_name | Nonparametric statistics |
| concepts[23].id | https://openalex.org/C127413603 |
| concepts[23].level | 0 |
| concepts[23].score | 0.28088945150375366 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[23].display_name | Engineering |
| concepts[24].id | https://openalex.org/C79061980 |
| concepts[24].level | 2 |
| concepts[24].score | 0.2804531753063202 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q941680 |
| concepts[24].display_name | Inertial measurement unit |
| concepts[25].id | https://openalex.org/C102519508 |
| concepts[25].level | 2 |
| concepts[25].score | 0.27747854590415955 |
| concepts[25].wikidata | https://www.wikidata.org/wiki/Q6520159 |
| concepts[25].display_name | Fourier transform |
| concepts[26].id | https://openalex.org/C197055811 |
| concepts[26].level | 2 |
| concepts[26].score | 0.26741278171539307 |
| concepts[26].wikidata | https://www.wikidata.org/wiki/Q207522 |
| concepts[26].display_name | Probability density function |
| concepts[27].id | https://openalex.org/C53533937 |
| concepts[27].level | 3 |
| concepts[27].score | 0.26676782965660095 |
| concepts[27].wikidata | https://www.wikidata.org/wiki/Q185020 |
| concepts[27].display_name | Histogram |
| concepts[28].id | https://openalex.org/C110083411 |
| concepts[28].level | 2 |
| concepts[28].score | 0.2608064115047455 |
| concepts[28].wikidata | https://www.wikidata.org/wiki/Q1744628 |
| concepts[28].display_name | Statistical classification |
| concepts[29].id | https://openalex.org/C145565327 |
| concepts[29].level | 3 |
| concepts[29].score | 0.2579044997692108 |
| concepts[29].wikidata | https://www.wikidata.org/wiki/Q852514 |
| concepts[29].display_name | Motion control |
| concepts[30].id | https://openalex.org/C17500928 |
| concepts[30].level | 2 |
| concepts[30].score | 0.25136059522628784 |
| concepts[30].wikidata | https://www.wikidata.org/wiki/Q959968 |
| concepts[30].display_name | Control system |
| concepts[31].id | https://openalex.org/C89805583 |
| concepts[31].level | 2 |
| concepts[31].score | 0.2500520944595337 |
| concepts[31].wikidata | https://www.wikidata.org/wiki/Q192940 |
| concepts[31].display_name | Accelerometer |
| keywords[0].id | https://openalex.org/keywords/correctness |
| keywords[0].score | 0.5834865570068359 |
| keywords[0].display_name | Correctness |
| keywords[1].id | https://openalex.org/keywords/estimator |
| keywords[1].score | 0.5210973024368286 |
| keywords[1].display_name | Estimator |
| keywords[2].id | https://openalex.org/keywords/vital-signs |
| keywords[2].score | 0.48369747400283813 |
| keywords[2].display_name | Vital signs |
| keywords[3].id | https://openalex.org/keywords/kernel-density-estimation |
| keywords[3].score | 0.43586957454681396 |
| keywords[3].display_name | Kernel density estimation |
| keywords[4].id | https://openalex.org/keywords/remote-patient-monitoring |
| keywords[4].score | 0.4062146544456482 |
| keywords[4].display_name | Remote patient monitoring |
| keywords[5].id | https://openalex.org/keywords/acceleration |
| keywords[5].score | 0.3862236738204956 |
| keywords[5].display_name | Acceleration |
| keywords[6].id | https://openalex.org/keywords/waveform |
| keywords[6].score | 0.3711758255958557 |
| keywords[6].display_name | Waveform |
| keywords[7].id | https://openalex.org/keywords/signal-processing |
| keywords[7].score | 0.3531641364097595 |
| keywords[7].display_name | Signal processing |
| keywords[8].id | https://openalex.org/keywords/classifier |
| keywords[8].score | 0.35018572211265564 |
| keywords[8].display_name | Classifier (UML) |
| language | en |
| locations[0].id | doi:10.3390/s25237391 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S101949793 |
| locations[0].source.issn | 1424-8220 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1424-8220 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Sensors |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/1424-8220/25/23/7391/pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Sensors |
| locations[0].landing_page_url | https://doi.org/10.3390/s25237391 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A1988001251 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-5120-0457 |
| authorships[0].author.display_name | Krzysztof Konopko |
| authorships[0].countries | PL |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I1323121030 |
| authorships[0].affiliations[0].raw_affiliation_string | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| authorships[0].institutions[0].id | https://openalex.org/I1323121030 |
| authorships[0].institutions[0].ror | https://ror.org/02bzfsy61 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I1323121030 |
| authorships[0].institutions[0].country_code | PL |
| authorships[0].institutions[0].display_name | Bialystok University of Technology |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Krzysztof Konopko |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| authorships[1].author.id | https://openalex.org/A1897162345 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-5183-6017 |
| authorships[1].author.display_name | Dariusz Janczak |
| authorships[1].countries | PL |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I1323121030 |
| authorships[1].affiliations[0].raw_affiliation_string | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| authorships[1].institutions[0].id | https://openalex.org/I1323121030 |
| authorships[1].institutions[0].ror | https://ror.org/02bzfsy61 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I1323121030 |
| authorships[1].institutions[0].country_code | PL |
| authorships[1].institutions[0].display_name | Bialystok University of Technology |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Dariusz Janczak |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| authorships[2].author.id | https://openalex.org/A236114405 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-2607-0619 |
| authorships[2].author.display_name | Wojciech Walendziuk |
| authorships[2].countries | PL |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I1323121030 |
| authorships[2].affiliations[0].raw_affiliation_string | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| authorships[2].institutions[0].id | https://openalex.org/I1323121030 |
| authorships[2].institutions[0].ror | https://ror.org/02bzfsy61 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I1323121030 |
| authorships[2].institutions[0].country_code | PL |
| authorships[2].institutions[0].display_name | Bialystok University of Technology |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Wojciech Walendziuk |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/1424-8220/25/23/7391/pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-12-05T00:00:00 |
| display_name | Implementation of Vital Signs Detection Algorithm for Supervising the Evacuation of Individuals with Special Needs |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-12-06T23:10:59.065948 |
| primary_topic.id | https://openalex.org/T11196 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.28277474641799927 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2204 |
| primary_topic.subfield.display_name | Biomedical Engineering |
| primary_topic.display_name | Non-Invasive Vital Sign Monitoring |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.3390/s25237391 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S101949793 |
| best_oa_location.source.issn | 1424-8220 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1424-8220 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Sensors |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/1424-8220/25/23/7391/pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Sensors |
| best_oa_location.landing_page_url | https://doi.org/10.3390/s25237391 |
| primary_location.id | doi:10.3390/s25237391 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S101949793 |
| primary_location.source.issn | 1424-8220 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1424-8220 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Sensors |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/1424-8220/25/23/7391/pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Sensors |
| primary_location.landing_page_url | https://doi.org/10.3390/s25237391 |
| publication_date | 2025-12-04 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 3, 40, 63, 159 |
| abstract_inverted_index.an | 197 |
| abstract_inverted_index.be | 211 |
| abstract_inverted_index.by | 101, 179 |
| abstract_inverted_index.in | 45, 72 |
| abstract_inverted_index.is | 50, 99, 116, 143 |
| abstract_inverted_index.of | 10, 20, 66, 75, 87, 90, 105, 111, 137, 162, 167, 176, 199, 208 |
| abstract_inverted_index.on | 52, 158 |
| abstract_inverted_index.to | 133 |
| abstract_inverted_index.95% | 194 |
| abstract_inverted_index.For | 29 |
| abstract_inverted_index.The | 0, 48, 93, 152, 171, 190 |
| abstract_inverted_index.and | 26, 39, 61, 108, 139, 187, 196 |
| abstract_inverted_index.can | 210 |
| abstract_inverted_index.for | 5, 145, 215 |
| abstract_inverted_index.its | 203 |
| abstract_inverted_index.key | 15 |
| abstract_inverted_index.the | 7, 24, 32, 35, 46, 56, 67, 73, 97, 103, 109, 112, 119, 131, 165, 168 |
| abstract_inverted_index.Fast | 57 |
| abstract_inverted_index.This | 80, 129, 206 |
| abstract_inverted_index.form | 74 |
| abstract_inverted_index.high | 204 |
| abstract_inverted_index.rest | 138 |
| abstract_inverted_index.skin | 98, 184 |
| abstract_inverted_index.were | 156 |
| abstract_inverted_index.with | 23, 96 |
| abstract_inverted_index.(FFT) | 60 |
| abstract_inverted_index.(PDF) | 71 |
| abstract_inverted_index.axes. | 128 |
| abstract_inverted_index.based | 51 |
| abstract_inverted_index.fully | 213 |
| abstract_inverted_index.group | 161 |
| abstract_inverted_index.level | 207 |
| abstract_inverted_index.light | 107 |
| abstract_inverted_index.pulse | 17, 30, 182 |
| abstract_inverted_index.skin, | 25 |
| abstract_inverted_index.three | 14, 127 |
| abstract_inverted_index.using | 55, 118 |
| abstract_inverted_index.vital | 8, 88, 148, 177 |
| abstract_inverted_index.which | 123, 142, 155, 201 |
| abstract_inverted_index.(KDE). | 79 |
| abstract_inverted_index.Kernel | 76 |
| abstract_inverted_index.Motion | 114 |
| abstract_inverted_index.across | 126 |
| abstract_inverted_index.allows | 130 |
| abstract_inverted_index.during | 150 |
| abstract_inverted_index.motion | 27, 188 |
| abstract_inverted_index.nearly | 193 |
| abstract_inverted_index.sensor | 38 |
| abstract_inverted_index.signal | 41 |
| abstract_inverted_index.states | 136 |
| abstract_inverted_index.study. | 47 |
| abstract_inverted_index.system | 4, 33, 132, 172 |
| abstract_inverted_index.wrist. | 113 |
| abstract_inverted_index.0.9465, | 200 |
| abstract_inverted_index.Density | 77 |
| abstract_inverted_index.Fourier | 58 |
| abstract_inverted_index.article | 1 |
| abstract_inverted_index.between | 135 |
| abstract_inverted_index.contact | 22, 95, 185 |
| abstract_inverted_index.crucial | 144 |
| abstract_inverted_index.density | 69 |
| abstract_inverted_index.employs | 34 |
| abstract_inverted_index.enables | 84 |
| abstract_inverted_index.ensures | 173 |
| abstract_inverted_index.module, | 122 |
| abstract_inverted_index.optical | 37 |
| abstract_inverted_index.precise | 181 |
| abstract_inverted_index.F1-score | 198 |
| abstract_inverted_index.MAX30102 | 36 |
| abstract_inverted_index.MPU-9250 | 120 |
| abstract_inverted_index.accuracy | 195 |
| abstract_inverted_index.achieved | 117 |
| abstract_inverted_index.achieves | 192 |
| abstract_inverted_index.analysis | 54 |
| abstract_inverted_index.analyzes | 124 |
| abstract_inverted_index.function | 70 |
| abstract_inverted_index.inertial | 121 |
| abstract_inverted_index.physical | 140 |
| abstract_inverted_index.quality. | 205 |
| abstract_inverted_index.reliable | 85, 174 |
| abstract_inverted_index.spectral | 53 |
| abstract_inverted_index.studies, | 154 |
| abstract_inverted_index.systems. | 218 |
| abstract_inverted_index.verified | 100 |
| abstract_inverted_index.Transform | 59 |
| abstract_inverted_index.activity, | 141 |
| abstract_inverted_index.algorithm | 43, 49, 83 |
| abstract_inverted_index.analysis. | 189 |
| abstract_inverted_index.combining | 180 |
| abstract_inverted_index.confirmed | 164 |
| abstract_inverted_index.describes | 2 |
| abstract_inverted_index.detection | 115 |
| abstract_inverted_index.developed | 81, 169 |
| abstract_inverted_index.estimator | 65 |
| abstract_inverted_index.evacuated | 11, 91 |
| abstract_inverted_index.indicates | 202 |
| abstract_inverted_index.measuring | 102 |
| abstract_inverted_index.performed | 157 |
| abstract_inverted_index.presented | 44 |
| abstract_inverted_index.real-time | 82 |
| abstract_inverted_index.wristband | 21, 94 |
| abstract_inverted_index.Estimation | 78 |
| abstract_inverted_index.accurately | 146 |
| abstract_inverted_index.algorithm. | 170 |
| abstract_inverted_index.assessment | 86 |
| abstract_inverted_index.brightness | 104 |
| abstract_inverted_index.classifier | 191 |
| abstract_inverted_index.considered | 212 |
| abstract_inverted_index.detection, | 18, 31, 183 |
| abstract_inverted_index.evacuation | 216 |
| abstract_inverted_index.monitoring | 6, 175, 217 |
| abstract_inverted_index.parameters | 9, 89, 149, 178 |
| abstract_inverted_index.processing | 42 |
| abstract_inverted_index.correctness | 166 |
| abstract_inverted_index.distinguish | 134 |
| abstract_inverted_index.evacuation. | 151 |
| abstract_inverted_index.integrating | 13 |
| abstract_inverted_index.probability | 68 |
| abstract_inverted_index.temperature | 110 |
| abstract_inverted_index.acceleration | 125 |
| abstract_inverted_index.experimental | 153 |
| abstract_inverted_index.incorporates | 62 |
| abstract_inverted_index.individuals, | 12, 163 |
| abstract_inverted_index.individuals. | 92 |
| abstract_inverted_index.interpreting | 147 |
| abstract_inverted_index.recognition. | 28 |
| abstract_inverted_index.satisfactory | 214 |
| abstract_inverted_index.verification | 19 |
| abstract_inverted_index.backscattered | 106 |
| abstract_inverted_index.effectiveness | 209 |
| abstract_inverted_index.nonparametric | 64 |
| abstract_inverted_index.verification, | 186 |
| abstract_inverted_index.representative | 160 |
| abstract_inverted_index.functionalities: | 16 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.69934857 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |