Reference Values of Regional Oxygen Saturation (rSO2) Determined by Near-Infrared Spectroscopy (NIRS) for 18 Selected Regions of Interest (ROIs) in Young and Elderly Healthy Volunteers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Volunteers
2.2. Research Procedures
2.2.1. Pre-Qualification Tests
2.2.2. Regional Oxygen Saturation (NIRS) and Body Composition (DXA) Measurements
2.3. Regional Oxygen Saturation (rSO2) Assessment
2.4. Body Composition Analysis
2.5. Statistical Analysis
3. Results
Characteristics of the Study Group
4. Discussion
5. Limitations of the Study
6. Novelty and Perspective
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Jöbsis, F.F. Noninvasive, Infrared Monitoring of Cerebral and Myocardial Oxygen Sufficiency and Circulatory Parameters. Science 1977, 198, 1264–1267. [Google Scholar] [CrossRef]
- Pintavirooj, C.; Ni, B.; Chatkobkool, C.; Pinijkij, K. Noninvasive Portable Hemoglobin Concentration Monitoring System Using Optical Sensor for Anemia Disease. Healthcare 2021, 9, 647. [Google Scholar] [CrossRef]
- Szucs, B.; Petrekanits, M.; Fekete, M.; Varga, J.T. The Use of Near-Infrared Spectroscopy for the Evaluation of a 4-Week Rehabilitation Program in Patients with COPD. Physiol. Int. 2021, 108, 427–439. [Google Scholar] [CrossRef]
- Ito, K.; Ookawara, S.; Uchida, T.; Hayasaka, H.; Kofuji, M.; Miyazawa, H.; Aomatsu, A.; Ueda, Y.; Hirai, K.; Morishita, Y. Measurement of Tissue Oxygenation Using Near-Infrared Spectroscopy in Patients Undergoing Hemodialysis. J. Vis. Exp. 2020, 164, e61721. [Google Scholar] [CrossRef]
- Boushel, R.; Piantadosi, C.A. Near-Infrared Spectroscopy for Monitoring Muscle Oxygenation. Acta Physiol. Scand. 2000, 168, 615–622. [Google Scholar] [CrossRef]
- Kovacsova, Z.; Bale, G.; Mitra, S.; de Roever, I.; Meek, J.; Robertson, N.; Tachtsidis, I. Investigation of Confounding Factors in Measuring Tissue Saturation with NIRS Spatially Resolved Spectroscopy. Adv. Exp. Med. Biol. 2018, 1072, 307–312. [Google Scholar] [CrossRef] [PubMed]
- Perel, A. Non-Invasive Monitoring of Oxygen Delivery in Acutely Ill Patients: New Frontiers. Ann. Intensive Care 2015, 5, 24. [Google Scholar] [CrossRef]
- Creteur, J.; Carollo, T.; Soldati, G.; Buchele, G.; De Backer, D.; Vincent, J.-L. The Prognostic Value of Muscle StO2 in Septic Patients. Intensive Care Med. 2007, 33, 1549–1556. [Google Scholar] [CrossRef]
- Ikossi, D.G.; Knudson, M.M.; Morabito, D.J.; Cohen, M.J.; Wan, J.J.; Khaw, L.; Stewart, C.J.; Hemphill, C.; Manley, G.T. Continuous Muscle Tissue Oxygenation in Critically Injured Patients: A Prospective Observational Study. J. Trauma Acute Care Surg. 2006, 61, 780–788. [Google Scholar] [CrossRef] [PubMed]
- Murkin, J.M.; Arango, M. Near-Infrared Spectroscopy as an Index of Brain and Tissue Oxygenation. Br. J. Anaesth. 2009, 103 (Suppl. S1), i3–i13. [Google Scholar] [CrossRef]
- Rodriguez, A.; Lisboa, T.; Martín-Loeches, I.; Díaz, E.; Trefler, S.; Restrepo, M.I.; Rello, J. Mortality and Regional Oxygen Saturation Index in Septic Shock Patients: A Pilot Study. J. Trauma Acute Care Surg. 2011, 70, 1145–1152. [Google Scholar] [CrossRef]
- Rodríguez, A.; Claverias, L.; Marín, J.; Magret, M.; Rosich, S.; Bodí, M.; Trefler, S.; Pascual, S.; Gea, J. Regional oxygen saturation index (rSO2) in brachioradialis and deltoid muscle. Correlation and prognosis in patients with respiratory sepsis. Med. Intensiva 2015, 39, 68–75. [Google Scholar] [CrossRef]
- Barstow, T.J. Understanding near Infrared Spectroscopy and Its Application to Skeletal Muscle Research. J. Appl. Physiol. 2019, 126, 1360–1376. [Google Scholar] [CrossRef]
- Chakravarti, S.; Srivastava, S.; Mittnacht, A.J.C. Near Infrared Spectroscopy (NIRS) in Children. Semin. Cardiothorac. Vasc. Anesth. 2008, 12, 70–79. [Google Scholar] [CrossRef]
- Howarth, C.; Banerjee, J.; Leung, T.; Aladangady, N. Could Near Infrared Spectroscopy (NIRS) Be the New Weapon in Our Fight against Necrotising Enterocolitis? Front. Pediatr. 2022, 10, 1024566. [Google Scholar] [CrossRef] [PubMed]
- Cui, W.; Kumar, C.; Chance, B. Experimental Study of Migration Depth for the Photons Measured at Sample Surface; Chance, B., Ed.; SPIE: Los Angeles, CA, USA, 1991; pp. 180–191. [Google Scholar]
- Strangman, G.; Boas, D.A.; Sutton, J.P. Non-Invasive Neuroimaging Using near-Infrared Light. Biol. Psychiatry 2002, 52, 679–693. [Google Scholar] [CrossRef] [PubMed]
- Taussky, P.; O’Neal, B.; Daugherty, W.P.; Luke, S.; Thorpe, D.; Pooley, R.A.; Evans, C.; Hanel, R.A.; Freeman, W.D. Validation of Frontal Near-Infrared Spectroscopy as Noninvasive Bedside Monitoring for Regional Cerebral Blood Flow in Brain-Injured Patients. Neurosurg. Focus 2012, 32, E2. [Google Scholar] [CrossRef] [PubMed]
- Ferreri, L.; Bigand, E.; Perrey, S.; Bugaiska, A. The Promise of Near-Infrared Spectroscopy (NIRS) for Psychological Research: A Brief Review. L’Année Psychol. 2014, 114, 537–569. [Google Scholar] [CrossRef]
- Dennis, J.J.; Wiggins, C.C.; Smith, J.R.; Isautier, J.M.J.; Johnson, B.D.; Joyner, M.J.; Cross, T.J. Measurement of Muscle Blood Flow and O2 Uptake via Near-Infrared Spectroscopy Using a Novel Occlusion Protocol. Sci. Rep. 2021, 11, 918. [Google Scholar] [CrossRef] [PubMed]
- Paulauskas, R.; Nekriošius, R.; Dadelienė, R.; Sousa, A.; Figueira, B. Muscle Oxygenation Measured with Near-Infrared Spectroscopy Following Different Intermittent Training Protocols in a World-Class Kayaker-A Case Study. Sensors 2022, 22, 8238. [Google Scholar] [CrossRef] [PubMed]
- Tuesta, M.; Yáñez-Sepúlveda, R.; Verdugo-Marchese, H.; Mateluna, C.; Alvear-Ordenes, I. Near-Infrared Spectroscopy Used to Assess Physiological Muscle Adaptations in Exercise Clinical Trials: A Systematic Review. Biology 2022, 11, 1073. [Google Scholar] [CrossRef]
- Malagoni, A.M.; Felisatti, M.; Mandini, S.; Mascoli, F.; Manfredini, R.; Basaglia, N.; Zamboni, P.; Manfredini, F. Resting Muscle Oxygen Consumption by Near-Infrared Spectroscopy in Peripheral Arterial Disease: A Parameter to Be Considered in a Clinical Setting? Angiology 2010, 61, 530–536. [Google Scholar] [CrossRef] [PubMed]
- Chuang, M.-L.; Lin, I.-F.; Hsieh, M.-J. More Impaired Dynamic Ventilatory Muscle Oxygenation in Congestive Heart Failure than in Chronic Obstructive Pulmonary Disease. J. Clin. Med. 2019, 8, 1641. [Google Scholar] [CrossRef] [PubMed]
- Sandberg, C.; Crenshaw, A.G.; Elçadi, G.H.; Christersson, C.; Hlebowicz, J.; Thilén, U.; Johansson, B. Patients with Complex Congenital Heart Disease Have Slower Calf Muscle Oxygenation during Exercise. Int. J. Cardiol. Congenit. Heart Dis. 2021, 4, 100157. [Google Scholar] [CrossRef]
- Lin, C.-K.; Leu, S.-W.; Tsai, Y.-H.; Zhou, S.-K.; Lin, C.-M.; Huang, S.-Y.; Chang, C.-C.; Ho, M.-C.; Lee, W.-C.; Chen, M.-C.; et al. Increased Tissue Water in Patients with Severe Sepsis Affects Tissue Oxygenation Measured by Near-Infrared Spectroscopy: A Prospective, Observational Case-Control Study. Quant. Imaging Med. Surg. 2022, 12, 4953–4967. [Google Scholar] [CrossRef] [PubMed]
- Tokue, H.; Tokue, A.; Tsushima, Y. rSO2 Measurement Using NIRS for Lower-Limb Blood Flow Monitoring and Estimation of Safe Balloon Occlusion/Deflation Time in Patients with PAS Who Underwent PBOA during CS. Medicina 2023, 59, 1146. [Google Scholar] [CrossRef]
- Boushel, R.; Langberg, H.; Olesen, J.; Gonzales-Alonzo, J.; Bülow, J.; Kjaer, M. Monitoring Tissue Oxygen Availability with near Infrared Spectroscopy (NIRS) in Health and Disease. Scand. J. Med. Sci. Sports 2001, 11, 213–222. [Google Scholar] [CrossRef]
- Chroboczek, M.; Jabłońska, A.; Kubiak, R.; Kujach, S.; Łuszczyk, M.; Laskowski, R. Usage of near Infrared Spectroscopy in Physiotherapy. Balt. J. Health Phys. Act. 2017, 9, 141–150. [Google Scholar] [CrossRef]
- Moriya, M.; Sakatani, K. Near Infrared Spectroscopy (NIRS) in Physical Medicine and Rehabilitation. Int. J. Phys. Med. Rehabil. 2021, 8, 586. [Google Scholar]
- Krugh, M.; Langaker, M.D. Dual-Energy X-Ray Absorptiometry. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2023. [Google Scholar]
- Rooke, T.W.; Hirsch, A.T.; Misra, S.; Sidawy, A.N.; Beckman, J.A.; Findeiss, L.K.; Golzarian, J.; Gornik, H.L.; Halperin, J.L.; Jaff, M.R.; et al. 2011 ACCF/AHA Focused Update of the Guideline for the Management of Patients With Peripheral Artery Disease (Updating the 2005 Guideline): A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J. Am. Coll. Cardiol. 2011, 58, 2020–2045. [Google Scholar] [CrossRef]
- Wanger, J.; Clausen, J.L.; Coates, A.; Pedersen, O.F.; Brusasco, V.; Burgos, F.; Casaburi, R.; Crapo, R.; Enright, P.; van der Grinten, C.P.M.; et al. Standardisation of the Measurement of Lung Volumes. Eur. Respir. J. 2005, 26, 511–522. [Google Scholar] [CrossRef] [PubMed]
- Bezemer, R.; Karemaker, J.M.; Klijn, E.; Martin, D.; Mitchell, K.; Grocott, M.; Heger, M.; Ince, C. Simultaneous Multi-Depth Assessment of Tissue Oxygen Saturation in Thenar and Forearm Using near-Infrared Spectroscopy during a Simple Cardiovascular Challenge. Crit. Care 2009, 13 (Suppl. S5), S5. [Google Scholar] [CrossRef] [PubMed]
- Payen, D.; Luengo, C.; Heyer, L.; Resche-Rigon, M.; Kerever, S.; Damoisel, C.; Losser, M.R. Is Thenar Tissue Hemoglobin Oxygen Saturation in Septic Shock Related to Macrohemodynamic Variables and Outcome? Crit. Care 2009, 13 (Suppl. S5), S6. [Google Scholar] [CrossRef]
- Lima, A.; van Bommel, J.; Jansen, T.C.; Ince, C.; Bakker, J. Low Tissue Oxygen Saturation at the End of Early Goal-Directed Therapy Is Associated with Worse Outcome in Critically Ill Patients. Crit. Care 2009, 13 (Suppl. S5), S13. [Google Scholar] [CrossRef]
- Hyttel-Sorensen, S.; Hessel, T.W.; Greisen, G. Peripheral Tissue Oximetry: Comparing Three Commercial near-Infrared Spectroscopy Oximeters on the Forearm. J. Clin. Monit. Comput. 2014, 28, 149–155. [Google Scholar] [CrossRef] [PubMed]
- Creteur, J. Muscle StO2 in Critically Ill Patients. Curr. Opin. Crit. Care 2008, 14, 361. [Google Scholar] [CrossRef] [PubMed]
- Ali, J.; Cody, J.; Maldonado, Y.; Ramakrishna, H. Near-Infrared Spectroscopy (NIRS) for Cerebral and Tissue Oximetry: Analysis of Evolving Applications. J. Cardiothorac. Vasc. Anesth. 2022, 36, 2758–2766. [Google Scholar] [CrossRef] [PubMed]
- Chen, S.; Wang, S.; Ding, S.; Zhang, C. Evaluation of Tibial Hemodynamic Response to Glucose Tolerance Test in Young Healthy Males and Females. Nutrients 2023, 15, 4062. [Google Scholar] [CrossRef]
- Corderfeldt Keiller, A.; Holmén, A.; Hansson, C.; Ricksten, S.-E.; Bragadottir, G.; Olofsson Bagge, R. Non-Invasive and Invasive Measurement of Skeletal Muscular Oxygenation during Isolated Limb Perfusion. Perfusion 2023, 38, 1019–1028. [Google Scholar] [CrossRef]
- Seddone, S.; Ermini, L.; Policastro, P.; Mesin, L.; Roatta, S. Evidence That Large Vessels Do Affect near Infrared Spectroscopy. Sci. Rep. 2022, 12, 2155. [Google Scholar] [CrossRef]
- Bretonneau, Q.; Bisschop, C.D.; Mons, V.; Pichon, A. Intercostal Muscle Oxygenation and Expiratory Loaded Breathing at Rest: Respiratory Pattern Effect. Respir. Physiol. Neurobiol. 2022, 304, 103925. [Google Scholar] [CrossRef] [PubMed]
- Ferrari, M.; Muthalib, M.; Quaresima, V. The Use of Near-Infrared Spectroscopy in Understanding Skeletal Muscle Physiology: Recent Developments. Philos. Trans. A Math. Phys. Eng. Sci. 2011, 369, 4577–4590. [Google Scholar] [CrossRef] [PubMed]
- Saxena, H.; Ward, K.R.; Krishnan, C.; Epureanu, B.I. Effect of Multi-Frequency Whole-Body Vibration on Muscle Activation, Metabolic Cost and Regional Tissue Oxygenation. IEEE Access 2020, 8, 140445. [Google Scholar] [CrossRef] [PubMed]
- Sendra-Pérez, C.; Sanchez-Jimenez, J.L.; Marzano-Felisatti, J.M.; Encarnación-Martínez, A.; Salvador-Palmer, R.; Priego-Quesada, J.I. Reliability of Threshold Determination Using Portable Muscle Oxygenation Monitors during Exercise Testing: A Systematic Review and Meta-Analysis. Sci. Rep. 2023, 13, 12649. [Google Scholar] [CrossRef] [PubMed]
- De Blasi, R.A.; Palmisani, S.; Alampi, D.; Mercieri, M.; Romano, R.; Collini, S.; Pinto, G. Microvascular Dysfunction and Skeletal Muscle Oxygenation Assessed by Phase-Modulation near-Infrared Spectroscopy in Patients with Septic Shock. Intensive Care Med. 2005, 31, 1661–1668. [Google Scholar] [CrossRef] [PubMed]
- Košir, M.; Možina, H.; Podbregar, M. Skeletal Muscle Oxygenation during Cardiopulmonary Resuscitation as a Predictor of Return of Spontaneous Circulation: A Pilot Study. Eur. J. Med. Res. 2023, 28, 418. [Google Scholar] [CrossRef]
- Plotkin, D.L.; Roberts, M.D.; Haun, C.T.; Schoenfeld, B.J. Muscle Fiber Type Transitions with Exercise Training: Shifting Perspectives. Sports 2021, 9, 127. [Google Scholar] [CrossRef]
- Koga, S.; Poole, D.C.; Fukuoka, Y.; Ferreira, L.F.; Kondo, N.; Ohmae, E.; Barstow, T.J. Methodological Validation of the Dynamic Heterogeneity of Muscle Deoxygenation within the Quadriceps during Cycle Exercise. Am. J. Physiol.-Regul. Integr. Comp. Physiol. 2011, 301, R534–R541. [Google Scholar] [CrossRef]
- Hendrickse, P.; Degens, H. The Role of the Microcirculation in Muscle Function and Plasticity. J. Muscle Res. Cell Motil. 2019, 40, 127–140. [Google Scholar] [CrossRef]
- Miller, B.F.; Olesen, J.L.; Hansen, M.; Døssing, S.; Crameri, R.M.; Welling, R.J.; Langberg, H.; Flyvbjerg, A.; Kjaer, M.; Babraj, J.A.; et al. Coordinated Collagen and Muscle Protein Synthesis in Human Patella Tendon and Quadriceps Muscle after Exercise. J. Physiol. 2005, 567, 1021–1033. [Google Scholar] [CrossRef]
- Calanni, L.; Zampella, C.; Micheletti, P.; Greco, D.; Negro, M.; D’Antona, G. Correlation between Patellar Tendon Mechanical Properties and Oxygenation Detection by Near Infrared Spectroscopy in Males. Muscle Ligaments Tendons J. 2021, 11, 54. [Google Scholar] [CrossRef]
- Kubo, K.; Ikebukuro, T.; Tsunoda, N.; Kanehisa, H. Changes in Oxygen Consumption of Human Muscle and Tendon Following Repeat Muscle Contractions. Eur. J. Appl. Physiol. 2008, 104, 859–866. [Google Scholar] [CrossRef]
- Palanca, A.A.; Yang, A.; Bishop, J.A. The Effects of Limb Elevation on Muscle Oxygen Saturation: A Near-Infrared Spectroscopy Study in Humans. PM&R 2016, 8, 221–224. [Google Scholar] [CrossRef]
- Soares, R.N.; Murias, J.M.; Saccone, F.; Puga, L.; Moreno, G.; Resnik, M.; De Roia, G.F. Effects of a Rehabilitation Program on Microvascular Function of CHD Patients Assessed by Near-Infrared Spectroscopy. Physiol. Rep. 2019, 7, e14145. [Google Scholar] [CrossRef] [PubMed]
- Bickler, P.E.; Feiner, J.R.; Rollins, M.D. Factors Affecting the Performance of 5 Cerebral Oximeters during Hypoxia in Healthy Volunteers. Anesth. Analg. 2013, 117, 813. [Google Scholar] [CrossRef] [PubMed]
- Robu, C.B.; Koninckx, A.; Docquier, M.-A.; Grosu, I.; De Kerchove, L.; Mastrobuoni, S.; Momeni, M. Advanced Age and Sex Influence Baseline Regional Cerebral Oxygen Saturation as Measured by Near-Infrared Spectroscopy: Subanalysis of a Prospective Study. J. Cardiothorac. Vasc. Anesth. 2020, 34, 3282–3289. [Google Scholar] [CrossRef] [PubMed]
- Bayareh-Mancilla, R.; Medina-Ramos, L.A.; Toriz-Vázquez, A.; Hernández-Rodríguez, Y.M.; Cigarroa-Mayorga, O.E. Automated Computer-Assisted Medical Decision-Making System Based on Morphological Shape and Skin Thickness Analysis for Asymmetry Detection in Mammographic Images. Diagnostics 2023, 13, 3440. [Google Scholar] [CrossRef] [PubMed]
- Shafique, S.; Tehsin, S. Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia. Comput. Math. Methods Med. 2018, 2018, 6125289. [Google Scholar] [CrossRef] [PubMed]
- Jahmunah, V.; Oh, S.L.; Wei, J.K.E.; Ciaccio, E.J.; Chua, K.; San, T.R.; Acharya, U.R. Computer-Aided Diagnosis of Congestive Heart Failure Using ECG Signals—A Review. Phys. Medica 2019, 62, 95–104. [Google Scholar] [CrossRef] [PubMed]
- Block, L.; El-Merhi, A.; Liljencrantz, J.; Naredi, S.; Staron, M.; Odenstedt Hergès, H. Cerebral Ischemia Detection Using Artificial Intelligence (CIDAI)—A Study Protocol. Acta Anaesthesiol. Scand. 2020, 64, 1335–1342. [Google Scholar] [CrossRef]
- Hu, X.-S.; Nascimento, T.D.; Bender, M.C.; Hall, T.; Petty, S.; O’Malley, S.; Ellwood, R.P.; Kaciroti, N.; Maslowski, E.; DaSilva, A.F. Feasibility of a Real-Time Clinical Augmented Reality and Artificial Intelligence Framework for Pain Detection and Localization From the Brain. J. Med. Internet Res. 2019, 21, e13594. [Google Scholar] [CrossRef] [PubMed]
- Le, A.S.; Aoki, H.; Murase, F.; Ishida, K. A Novel Method for Classifying Driver Mental Workload Under Naturalistic Conditions With Information From Near-Infrared Spectroscopy. Front. Hum. Neurosci. 2018, 12, 431. [Google Scholar] [CrossRef] [PubMed]
- Asgher, U.; Khalil, K.; Khan, M.J.; Ahmad, R.; Butt, S.I.; Ayaz, Y.; Naseer, N.; Nazir, S. Enhanced Accuracy for Multiclass Mental Workload Detection Using Long Short-Term Memory for Brain-Computer Interface. Front. Neurosci. 2020, 14, 584. [Google Scholar] [CrossRef] [PubMed]
Study Group n = 70 (♀ = 51, ♂ = 19) | Young Group n = 30 (♀ = 18, ♂ = 12) | Older Group n = 40 (♀ = 33, ♂ = 7) | Mann–Whitney U Test | ||||||
---|---|---|---|---|---|---|---|---|---|
Median | Min–Max | Median | Min–Max | Median | Min–Max | z | p | ||
Age [years] | 64 | 20–79 | 23 | 20–30 | 70 | 60–79 | −7.16 | 0.000 | |
Weight [kg] | 71 | 46–115 | 66.50 | 46–115 | 72.5 | 49–94 | −1.61 | 0.079 | |
Height [cm] | 165.00 | 150.5–196 | 169.25 | 163–196 | 163 | 150.5–185 | 4.38 | 0.000 | |
BMI [kg/m2] | 26.24 | 16.2–38.7 | 22.42 | 16.21–38.88 | 27.74 | 20.13–37.8 | −4.38 | 0.000 | |
FM [kg] | 26.29 | 10.20–55.85 | 20.50 | 10.21–53.93 | 28.14 | 12.76–55.85 | −3.94 | 0.000 | |
PBF [%] | 36.3 | 17.02–49.33 | 31.48 | 17.03–49.34 | 39.79 | 20.77–47.17 | −4.12 | 0.000 | |
WBSAT [kg] | 1.40 | 0.24–3.45 | 0.93 | 0.24–3.08 | 1.52 | 0.66–3.45 | −4.30 | 0.000 | |
SPO2 | 97.5 | 92–100 | 98 | 94–100 | 97 | 92–99 | 3.79 | 0.000 | |
HR | 74.5 | 53–116 | 74.5 | 53–100 | 74 | 57–116 | −0.49 | 0.622 | |
ABI | L | 1.17 | 0.9–1.36 | 1.17 | 1.07–1.31 | 1.16 | 0.9–1.36 | −0.15 | 0.884 |
P | 1.19 | 0.9–1.39 | 1.19 | 1.05–1.39 | 1.18 | 0.9–1.36 | 0.51 | 0.610 | |
VCmax | 3.52 | 1.6–7.31 | 4.45 | 2.57–7.31 | 3.03 | 1.6–5.18 | 5.25 | 0.000 | |
VCin | 3.52 | 1.38–7.31 | 4.45 | 1.91–7.31 | 2.99 | 1.38–4.97 | 4.82 | 0.000 | |
VCex | 2.77 | 0.77–7.01 | 3.72 | 1.51–7.01 | 2.09 | 0.77–5.18 | 4.45 | 0.000 | |
IC | 2.59 | 1.23–8.91 | 3.17 | 1.42–5.54 | 2.44 | 1.23–8.92 | 3.57 | 0.000 | |
IRV | 1.67 | 0.2–4.22 | 2.07 | 0.25–4.22 | 1.39 | 0.2–2.72 | 3.50 | 0.000 | |
VT | 1.00 | 0.4–8.04 | 1.02 | 0.4–3.08 | 0.93 | 0.44–8.04 | 1.12 | 0.263 | |
ERV | 0.88 | 0.11–6.98 | 1.33 | 0.33–2.39 | 0.65 | 0.11–6.98 | 4.82 | 0.000 |
Young Group n = 30 | t-Test | Older Group n = 40 | t-Test | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Mean [%] | ±SD | t | p | Mean [%] | ±SD | t | p | |||
Head | Forehead | L | 70.67 | 4.50 | −0.23 | 0.819 | 64.73 | 7.31 | −1.28 | 0.206 |
R | 70.97 | 5.54 | 66.70 | 6.52 | ||||||
Neck | Middle neck | L | 73.03 | 6.00 | 0.40 | 0.689 | 67.80 | 5.74 | 0.10 | 0.924 |
R | 72.47 | 4.88 | 67.68 | 5.89 | ||||||
Trunk | Trapezius | L | 71.97 | 4.25 | −0.18 | 0.860 | 67.30 | 7.94 | −0.03 | 0.975 |
R | 72.20 | 5.86 | 67.35 | 6.25 | ||||||
C-Th | L | 66.60 | 7.38 | −0.15 | 0.882 | 61.75 | 7.93 | 0.98 | 0.330 | |
R | 72.20 | 6.46 | 60.03 | 7.82 | ||||||
Th-L | L | 69.37 | 7.23 | −0.34 | 0.737 | 62.63 | 7.23 | −0.20 | 0.843 | |
R | 69.97 | 6.55 | 62.95 | 7.41 | ||||||
L-S | L | 67.90 | 7.58 | 0.40 | 0.694 | 64.65 | 5.14 | −0.74 | 0.459 | |
R | 67.07 | 8.69 | 65.50 | 5.08 | ||||||
Upper limb | Wrist extensors | L | 66.87 | 7.85 | −0.31 | 0.757 | 65.43 | 7.26 | −0.14 | 0.888 |
R | 67.57 | 9.52 | 65.65 | 6.97 | ||||||
Cubital fossa | L | 67.07 | 7.24 | −0.04 | 0.970 | 64.53 | 8.30 | −1.47 | 0.146 | |
R | 67.13 | 6.20 | 66.95 | 6.34 | ||||||
Carpal tunnel | L | 52.93 | 11.93 | −0.11 | 0.910 | 61.68 | 10.44 | 2.60 | 0.011 | |
R | 53.27 | 10.76 | 56.33 | 7.78 | ||||||
Lower limb | Femoral triangle | L | 69.00 | 9.24 | 0.30 | 0.769 | 60.70 | 8.83 | −0.10 | 0.921 |
R | 68.27 | 9.99 | 60.90 | 9.08 | ||||||
Rectus femoris | L | 66.50 | 9.86 | 0.47 | 0.639 | 61.75 | 8.22 | −0.19 | 0.847 | |
R | 65.37 | 8.74 | 62.10 | 7.91 | ||||||
Tibialis anterior | L | 70.13 | 8.96 | 0.21 | 0.835 | 69.53 | 5.51 | −0.76 | 0.447 | |
R | 69.57 | 11.82 | 70.48 | 5.59 | ||||||
Ankle joint | L | 43.80 | 14.37 | −0.71 | 0.482 | 52.69 | 10.58 | −0.80 | 0.429 | |
R | 46.62 | 16.20 | 54.59 | 10.49 | ||||||
Biceps femoris | L | 64.03 | 6.61 | 0.25 | 0.807 | 63.75 | 8.55 | −0.24 | 0.807 | |
R | 63.57 | 8.06 | 64.20 | 7.89 | ||||||
Popliteal fossa | L | 62.83 | 10.00 | −0.23 | 0.818 | 59.65 | 8.29 | 0.10 | 0.917 | |
R | 63.47 | 11.14 | 59.45 | 8.88 | ||||||
Gastrocnemius | L | 65.63 | 9.41 | 0.68 | 0.499 | 64.65 | 7.91 | −0.33 | 0.743 | |
R | 63.57 | 13.73 | 65.25 | 8.42 | ||||||
Achilles tendon | L | 27.40 | 18.46 | −0.84 | 0.403 | 51.43 | 14.46 | 1.84 | 0.070 | |
R | 31.43 | 18.63 | 45.65 | 13.64 | ||||||
Plantar fascia | L | 56.23 | 11.30 | −0.20 | 0.842 | 61.58 | 12.04 | −0.20 | 0.845 | |
R | 56.80 | 10.57 | 62.10 | 11.93 |
Study Group n = 70 | Young Group n = 30 | Older Group n = 40 | t-Test | ||||||
---|---|---|---|---|---|---|---|---|---|
Mean [%] | ±SD | Mean [%] | ±SD | Mean [%] | ±SD | t | p | ||
Head | Forehead | 67.72 | 6.37 | 67.72 | 6.37 | 65.40 | 6.68 | 3.86 | 0.000 |
Gini index | 0.081 | 0.101 | 0.107 | ||||||
Neck | Middle neck | 69.89 | 6.05 | 69.89 | 6.05 | 67.74 | 5.76 | 3.74 | 0.000 |
Gini index | 0.076 | 0.105 | 0.096 | ||||||
Trunk | Trapezius | 69.36 | 6.35 | 69.36 | 6.35 | 67.33 | 6.71 | 3.32 | 0.001 |
Gini index | 0.078 | 0.102 | 0.104 | ||||||
C-Th | 63.39 | 7.73 | 63.39 | 7.73 | 60.89 | 7.63 | 3.36 | 0.001 | |
Gini index | 0.097 | 0.122 | 0.119 | ||||||
Th-L | 65.74 | 7.76 | 65.74 | 7.76 | 62.79 | 7.20 | 4.06 | 0.000 | |
Gini index | 0.097 | 0.117 | 0.110 | ||||||
L-S | 66.11 | 6.43 | 66.11 | 6.43 | 65.08 | 4.87 | 1.57 | 0.122 | |
Gini index | 0.087 | 0.131 | 0.091 | ||||||
Upper limb | Wrist extensors | 66.26 | 7.46 | 66.26 | 7.46 | 65.54 | 6.72 | 0.93 | 0.355 |
Gini index | 0.09 | 0.135 | 0.104 | ||||||
Cubital fossa | 66.32 | 6.28 | 66.32 | 6.28 | 65.74 | 6.46 | 0.90 | 0.373 | |
Gini index | 0.082 | 0.116 | 0.105 | ||||||
Carpal tunnel | 56.47 | 9.69 | 56.47 | 9.69 | 59.00 | 8.37 | −2.63 | 0.011 | |
0.125 | 0.177 | 0.128 | |||||||
Lower limb | Femoral triangle | 64.16 | 9.74 | 64.16 | 9.74 | 60.80 | 8.84 | 3.61 | 0.001 |
Gini index | 0.114 | 0.14 | 0.130 | ||||||
Rectus femoris | 63.64 | 8.62 | 63.64 | 8.62 | 61.93 | 7.89 | 1.96 | 0.054 | |
Gini index | 0.103 | 0.139 | 0.120 | ||||||
Tibialis anterior | 69.94 | 6.93 | 69.94 | 6.93 | 70.00 | 5.26 | −0.09 | 0.929 | |
Gini index | 0.081 | 0.131 | 0.091 | ||||||
Ankle joint | 49.80 | 12.76 | 49.80 | 12.76 | 53.64 | 9.25 | −3.02 | 0.004 | |
Gini index | 0.168 | 0.244 | 0.146 | ||||||
Biceps femoris | 63.90 | 7.54 | 63.90 | 7.54 | 63.98 | 8.00 | −0.10 | 0.924 | |
Gini index | 0.093 | 0.128 | 0.116 | ||||||
Popliteal fossa | 61.09 | 9.12 | 61.09 | 9.12 | 59.55 | 7.85 | 1.66 | 0.102 | |
Gini index | 0.108 | 0.152 | 0.120 | ||||||
Gastrocnemius | 64.80 | 8.60 | 64.80 | 8.60 | 64.95 | 7.80 | −0.17 | 0.868 | |
Gini index | 0.102 | 0.148 | 0.117 | ||||||
Achilles tendon | 40.34 | 17.65 | 40.34 | 17.65 | 48.54 | 13.33 | −5.29 | 0.000 | |
Gini index | 0.275 | 0.388 | 0.201 | ||||||
Plantar fascia | 59.71 | 11.90 | 67.72 | 6.37 | 61.99 | 12.15 | −1.81 | 0.075 | |
Gini index | 0.139 | 0.173 | 0.156 |
Women n = 51 | Men n = 19 | t-Test | |||||
---|---|---|---|---|---|---|---|
Mean [%] | ±SD | Mean [%] | ±SD | t | p | ||
Head | Forehead | 66.75 | 6.48 | 70.33 | 5.39 | −2.15 | 0.035 |
Neck | Middle neck | 68.76 | 5.98 | 72.89 | 5.30 | −2.65 | 0.010 |
Trunk | Trapezius | 68.91 | 6.40 | 70.58 | 6.20 | −0.98 | 0.332 |
C-Th | 62.77 | 8.29 | 65.05 | 5.86 | −1.10 | 0.276 | |
Th-L | 65.09 | 8.33 | 67.47 | 5.80 | −1.15 | 0.256 | |
L-S | 65.31 | 5.99 | 68.24 | 7.22 | −1.72 | 0.091 | |
Upper limb | Wrist extensors | 65.15 | 7.63 | 69.24 | 6.20 | −2.09 | 0.040 |
Cubital fossa | 66.22 | 6.38 | 66.61 | 6.16 | −0.23 | 0.819 | |
Carpal tunnel | 55.54 | 9.93 | 58.97 | 8.81 | −1.33 | 0.190 | |
Lower limb | Femoral triangle | 63.25 | 9.95 | 66.61 | 8.95 | −1.29 | 0.202 |
Rectus femoris | 61.55 | 7.72 | 69.26 | 8.59 | −3.61 | 0.001 | |
Tibialis anterior | 69.56 | 6.42 | 70.95 | 8.25 | −0.75 | 0.460 | |
Ankle joint | 50.92 | 12.53 | 46.84 | 13.25 | 1.19 | 0.239 | |
Biceps femoris | 62.85 | 7.17 | 66.71 | 7.98 | −1.95 | 0.056 | |
Popliteal fossa | 59.38 | 9.27 | 65.68 | 7.04 | −2.69 | 0.009 | |
Gastrocnemius | 64.10 | 8.23 | 66.68 | 9.50 | −1.13 | 0.266 | |
Achilles tendon | 44.16 | 15.56 | 30.11 | 19.23 | 3.15 | 0.002 | |
Plantar fascia | 60.21 | 11.74 | 58.39 | 12.53 | 0.57 | 0.575 |
ROI | Neck | Trunk | Upper Limb | Lower Limb | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Middle Neck | Trapezius | C-Th | Th-L | L-S | Wrist Extensors | Cubital Fossa | Carpal Tunnel | Femoral Triangle | Rectus Femoris | Tibialis Anterior | Ankle Joint | Biceps Femoris | Popliteal Fossa | Gastrocnemius | Achilles Tendon | Plantar Fascia | |||
Head | Forehead | Y + O | −2.59 * | −1.83 | 5.13 *** | 2.49 * | 2.25 * | 1.89 | 1.91 | 10.74 *** | 3.70 *** | 4.57 *** | −2.32 * | 14.13 *** | 4.61 *** | 6.91 *** | 3.10 * | 16.39 *** | 7.31 *** |
Y | −2.03 * | −1.38 | 3.72 *** | 1.05 | 2.71 ** | 2.79** | 3.45 ** | 11.14 *** | 1.57 | 3.59 *** | 0.65 | 12.38 *** | 6.13 *** | 5.11 *** | 3.78 *** | 16.73 *** | 9.27 *** | ||
O | −2.00 * | −1.45 | 4.11 *** | 2.60 * | 0.66 | 0.16 | −0.02 | 5.09 *** | 3.89 *** | 3.19 ** | −4.31 *** | 8.53 *** | 1.45 | 5.01 *** | 0.64 | 9.68 *** | 2.51 * | ||
Neck | Middle neck | Y + O | x | 0.68 | 7.63 *** | 4.93 *** | 4.95 *** | 4.32*** | 4.48 *** | 12.88 *** | 5.80 *** | 6.90 *** | −0.06 | 15.95 *** | 7.14 *** | 9.16 *** | 5.21 *** | 17.73 *** | 9.23 *** |
Y | x | 0.69 | 5.32 *** | 2.73 ** | 4.19 *** | 4.19*** | 5.08 *** | 12.18 *** | 2.90 ** | 4.92 *** | 1.91 | 13.20 *** | 7.61 *** | 6.29 *** | 4.89 *** | 17.41 *** | 10.36 *** | ||
O | x | 0.4 | 6.27 *** | 4.77 *** | 3.09 ** | 2.15* | 1.9 | 7.01 *** | 5.85 *** | 5.26 *** | −2.53 * | 10.48 *** | 3.36 ** | 7.10 *** | 2.50 ** | 11.16 *** | 3.99 *** | ||
Trunk | Trapezius | Y + O | x | 6.77 *** | 4.15 *** | 4.08 *** | 3.57*** | 3.67 *** | 12.09 *** | 5.13 *** | 6.13 *** | −0.65 | 15.27 *** | 6.28 *** | 8.37 *** | 4.55 *** | 17.25 *** | 8.58 *** | |
Y | x | 4.85 *** | 2.20 * | 3.73 *** | 3.76*** | 4.60 *** | 11.90 *** | 2.47 * | 4.51 *** | 1.49 | 12.97 *** | 7.21 *** | 5.93 *** | 4.54 *** | 17.23 *** | 10.06 *** | |||
O | x | 5.43 *** | 3.99 *** | 2.30 * | 1.6 | 1.38 | 6.26 *** | 5.13 *** | 4.51 *** | −2.66 ** | 9.61 *** | 2.77 ** | 6.26 *** | 1.97 | 10.54 *** | 3.54 ** | |||
C-Th | Y + O | x | −2.48 * | −3.09 ** | 3.04** | 3.24 ** | −6.14 *** | −0.71 | −0.25 | −6.87 *** | 10.14 *** | −0.54 | 2.18 * | −1.32 | 13.39 *** | 3.20 ** | |||
Y | x | −2.34 * | −0.55 | 0.34 | 0.3 | −8.00 *** | −1.25 | 0.54 | −1.94 | 9.97 *** | 2.26 * | 2.21 * | 1.22 | 14.65 *** | 6.16 *** | ||||
O | x | −1.59 | −3.99 *** | 3.93*** | 4.01 *** | −1.37 | 0.07 | −0.83 | −8.47 *** | 4.91 *** | −2.43 * | 1.03 | −3.21 ** | 6.78 *** | −0.6 | ||||
Th-L | Y + O | x | −0.43 | 0.56 | 0.65 | −8.27 *** | 1.47 | 2.10 * | −4.44 *** | 11.97 *** | 1.96 | 4.44 *** | 0.88 | 14.79*** | 5.18*** | ||||
Y | x | 1.6 | −1.72 | −2.08 * | −9.74 *** | 0.68 | 2.51 * | −0.11 | 11.34 *** | 4.54*** | 4.03 * | 2.89** | 15.81 *** | 7.94 *** | |||||
O | x | −2.30 * | 2.42* | 2.54 ** | −2.82 ** | 1.55 | 0.71 | −7.05 *** | 6.37 *** | −0.97 | 2.58 ** | −1.77 | 7.96 *** | 0.61 | |||||
L-S | Y + O | x | 0.17 | 0.26 | −9.07 *** | 1.93 | 2.65 ** | −4.37 *** | 12.73 *** | 2.55 * | 5.10 *** | 1.31 | 15.34 *** | 5.75 *** | |||||
Y | x | −0.17 | −0.28 | −8.03 *** | −0.71 | 0.98 | −1.39 | 10.00 *** | 2.61 ** | 2.53 *** | 1.57 | 14.60 *** | 6.27 *** | ||||||
O | x | 0.47 | 0.66 | −5.03 *** | 3.73 *** | 2.97 ** | −5.85 *** | 8.73 *** | 1.02 | 4.97 *** | 0.12 | 9.76 *** | 2.24 * | ||||||
Upper limb | Wrist extensors | Y + O | x | −0.07 | 8.75 *** | 1.97 | 2.63 ** | −3.90 *** | 12.38 *** | 2.53 * | 4.95 *** | 1.38 | 15.11 *** | 5.63 *** | |||||
Y | x | 0.08 | 7.70 *** | −0.85 | 0.78 | −1.51 | 9.72 *** | 2.34 * | 2.31 * | 1.39 | 14.34 *** | 5.97 *** | |||||||
O | x | −0.17 | 4.93 *** | 3.73 *** | 3.02 ** | −4.44 *** | 8.37 *** | 1.29 | 4.83 *** | 0.49 | 9.55 *** | 2.39 * | |||||||
Cubital fossa | Y + O | x | 9.07 *** | 2.09 | 2.80 ** | −4.00 *** | 12.70 *** | 2.71 ** | 5.19 *** | 1.49 | 15.33 *** | 5.83 *** | |||||||
Y | x | 8.28 *** | −1.02 | 0.79 | −1.72 | 10.19 *** | 2.58 * | 2.46 * | 1.44 | 14.84 *** | 6.43 *** | ||||||||
O | x | 4.98 *** | 3.81 *** | 3.12 ** | −4.11 *** | 8.37 *** | 1.43 | 4.89 *** | 0.64 | 9.56 *** | 2.48 ** | ||||||||
Carpal tunnel | Y + O | x | −6.23 *** | −6.14 *** | −11.96 *** | 4.45 *** | −6.65 *** | −3.81 *** | −6.80 *** | 8.85 *** | −2.30 * | ||||||||
Y | x | −8.15 *** | −6.82 *** | −8.46 *** | 3.23 *** | −6.17 *** | −5.06 *** | −5.48 *** | 8.47 *** | −1.69 | |||||||||
O | x | −1.23 | −2.10 * | −8.92 *** | 3.36 ** | −3.54 ** | −0.38 | −4.25 *** | 5.45 *** | −1.66 | |||||||||
Lower limb | Femoral triangle | Y + O | x | 0.46 | −5.37 *** | 10.01 *** | 0.24 | 2.63 ** | −0.55 | 13.28 *** | 3.54 *** | ||||||||
Y | x | 1.57 | −0.67 | 10.08 *** | 3.11 ** | 2.99 ** | 2.07 * | 14.59 *** | 6.49 *** | ||||||||||
O | x | −0.84 | −7.85 *** | 4.62 *** | −2.35 * | 0.91 | −3.08 ** | 6.52 *** | −0.62 | ||||||||||
Rectus femoris | Y + O | x | −6.29 *** | 10.06 *** | −0.26 | 2.33 * | −1.04 | 13.33 *** | 3.30 ** | ||||||||||
Y | x | −2.18 * | 9.00 *** | 1.4 | 1.54 | 0.69 | 13.67 *** | 5.11 *** | |||||||||||
O | x | −7.41 *** | 5.58 *** | −1.6 | 1.81 | −2.37 * | 7.32 *** | 0.05 | |||||||||||
Tibialis anterior | Y + O | x | 15.11 *** | 6.41 *** | 8.41 *** | 4.82 *** | 17.20 *** | 8.66 *** | |||||||||||
Y | x | 10.33 *** | 3.69 *** | 3.51 ** | 2.60 * | 14.76 *** | 6.87 *** | ||||||||||||
O | x | 12.28 *** | 5.46 *** | 9.18 *** | 4.59 *** | 12.54 *** | 5.56 *** | ||||||||||||
Ankle joint | Y + O | x | −10.59 *** | −7.95 *** | −10.52 *** | 4.93 *** | −6.32 *** | ||||||||||||
Y | x | −8.52 *** | −7.50 *** | −7.80 *** | 5.07 *** | −4.68 *** | |||||||||||||
O | x | −6.91 *** | −3.88 *** | −7.58 *** | 2.55 ** | −4.58 *** | |||||||||||||
Biceps femoris | Y + O | x | 2.69 ** | −0.85 | 13.74 *** | 3.65 *** | |||||||||||||
Y | x | 0.39 | −0.45 | 13.39 *** | 4.31 *** | ||||||||||||||
O | x | 3.35 ** | −0.76 | 8.40 *** | 1.32 | ||||||||||||||
Popliteal fossa | Y + O | x | −3.21 ** | 11.67 *** | 1.2 | ||||||||||||||
Y | x | −0.71 | 12.28 *** | 3.40 ** | |||||||||||||||
O | x | −4.10 *** | 5.92 *** | −1.4 | |||||||||||||||
Gastrocnemius | Y + O | x | 13.69 *** | 4.06 *** | |||||||||||||||
Y | x | 12.45 *** | 3.92 *** | ||||||||||||||||
O | x | 8.94 *** | 1.93 | ||||||||||||||||
Achilles tendon | Y + O | x | −10.28 *** | ||||||||||||||||
Y | x | −9.79 *** | |||||||||||||||||
O | x | −6.40 *** |
rSO2 [%] | Age [Year] | BMI [kg/m2] | PBF [%] | WBSAT [kg] | FM [kg] | LM [kg] | |
---|---|---|---|---|---|---|---|
Head | |||||||
Head | Forehead | −0.45 *** | −0.12 | −0.10 | −0.12 | 0.17 | 0.07 |
Trunk | |||||||
Trunk | Middle neck | −0.39 ** | −0.44 *** | −0.38 ** | −0.34 ** | −0.32 ** | 0.09 |
Trapezius | −0.37 ** | −0.66 *** | −0.41 ** | −0.39 * | −0.40 *** | −0.03 | |
C-Th | −0.36 ** | −0.67 *** | −0.45 *** | −0.37 * | −0.36 * | −0.04 | |
Th-L | −0.45 *** | −0.70 *** | −0.51 *** | −0.47 *** | −0.50 *** | −0.13 | |
L-S | −0.19 | −0.45 *** | −0.45 *** | −0.43 *** | −0.42 *** | −0.03 | |
Upper limb | |||||||
Upper limb | Wrist extensors | −0.06 | −0.49 *** | −0.33 ** | −0.35 | 0.08 ** | 0.24 |
Cubital fossa | −0.14 | −0.22 | −0.32 ** | −0.21 * | −0.00 | 0.24 | |
Carpal tunnel | 0.29 | 0.33 ** | 0.07 | 0.19 | 0.13 | 0.18 | |
Lower limb | |||||||
Lower limb | Femoral triangle | −0.36 ** | −0.56 *** | −0.44 *** | −0.43 *** | −0.31 * | 0.17 |
Rectus femoris | −0.20 | −0.46 *** | −0.45 *** | −0.42 *** | −0.40 *** | 0.22 | |
Tibialis anterior | −0.06 | −0.45 *** | −0.40 ** | −0.42 *** | −0.46 *** | −0.11 | |
Ankle joint | 0.34 ** | 0.11 | 0.10 | 015 | −0.12 | −0.24 | |
Biceps femoris | 0.04 | −0.33 ** | −0.29 * | −0.24 | −0.38 ** | 0.12 | |
Popliteal fossa | −0.14 | −0.46 *** | −0.47 *** | −0.47 *** | −0.53 *** | 0.14 | |
Gastrocnemius | −0.01 | −0.31 ** | −0.50 *** | −0.28 * | −0.41 *** | 0.13 | |
Achilles tendon | 0.51 *** | 0.34 ** | 0.35 ** | 0.30 * | 0.01 | −0.37 ** | |
Plantar fascia | 0.22 | −0.04 | −0.07 | −0.78 | −0.21 | −0.06 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Lubkowska, A.; Radecka, A.; Pluta, W.; Wieleba, K. Reference Values of Regional Oxygen Saturation (rSO2) Determined by Near-Infrared Spectroscopy (NIRS) for 18 Selected Regions of Interest (ROIs) in Young and Elderly Healthy Volunteers. Appl. Sci. 2024, 14, 1307. https://doi.org/10.3390/app14031307
Lubkowska A, Radecka A, Pluta W, Wieleba K. Reference Values of Regional Oxygen Saturation (rSO2) Determined by Near-Infrared Spectroscopy (NIRS) for 18 Selected Regions of Interest (ROIs) in Young and Elderly Healthy Volunteers. Applied Sciences. 2024; 14(3):1307. https://doi.org/10.3390/app14031307
Chicago/Turabian StyleLubkowska, Anna, Aleksandra Radecka, Waldemar Pluta, and Krzysztof Wieleba. 2024. "Reference Values of Regional Oxygen Saturation (rSO2) Determined by Near-Infrared Spectroscopy (NIRS) for 18 Selected Regions of Interest (ROIs) in Young and Elderly Healthy Volunteers" Applied Sciences 14, no. 3: 1307. https://doi.org/10.3390/app14031307
APA StyleLubkowska, A., Radecka, A., Pluta, W., & Wieleba, K. (2024). Reference Values of Regional Oxygen Saturation (rSO2) Determined by Near-Infrared Spectroscopy (NIRS) for 18 Selected Regions of Interest (ROIs) in Young and Elderly Healthy Volunteers. Applied Sciences, 14(3), 1307. https://doi.org/10.3390/app14031307