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Moffat R, Casale CE, Cross ES. Mobile fNIRS for exploring inter-brain synchrony across generations and time. Front Neuroergon 2024; 4:1260738. [PMID: 38234472 PMCID: PMC10790948 DOI: 10.3389/fnrgo.2023.1260738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/01/2023] [Indexed: 01/19/2024]
Abstract
While still relatively rare, longitudinal hyperscanning studies are exceptionally valuable for documenting changes in inter-brain synchrony, which may in turn underpin how behaviors develop and evolve in social settings. The generalizability and ecological validity of this experimental approach hinges on the selected imaging technique being mobile-a requirement met by functional near-infrared spectroscopy (fNIRS). fNIRS has most frequently been used to examine the development of inter-brain synchrony and behavior in child-parent dyads. In this position paper, we contend that dedicating attention to longitudinal and intergenerational hyperscanning stands to benefit the fields of social and cognitive neuroscience more broadly. We argue that this approach is particularly relevant for understanding the neural mechanisms underpinning intergenerational social dynamics, and potentially for benchmarking progress in psychological and social interventions, many of which are situated in intergenerational contexts. In line with our position, we highlight areas of intergenerational research that stand to be enhanced by longitudinal hyperscanning with mobile devices, describe challenges that may arise from measuring across generations in the real world, and offer potential solutions.
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Affiliation(s)
- Ryssa Moffat
- Social Brain Sciences, ETH Zurich, Zurich, Switzerland
| | - Courtney E. Casale
- School of Psychological Sciences, Macquarie University, Sydney, NSW, Australia
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Shahbakhti M, Hakimi N, Horschig JM, Floor-Westerdijk M, Claassen J, Colier WNJM. Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System. Sensors (Basel) 2023; 23:3632. [PMID: 37050692 PMCID: PMC10099192 DOI: 10.3390/s23073632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
OBJECTIVE The employment of wearable systems for continuous monitoring of vital signs is increasing. However, due to substantial susceptibility of conventional bio-signals recorded by wearable systems to motion artifacts, estimation of the respiratory rate (RR) during physical activities is a challenging task. Alternatively, functional Near-Infrared Spectroscopy (fNIRS) can be used, which has been proven less vulnerable to the subject's movements. This paper proposes a fusion-based method for estimating RR during bicycling from fNIRS signals recorded by a wearable system. METHODS Firstly, five respiratory modulations are extracted, based on amplitude, frequency, and intensity of the oxygenated hemoglobin concentration (O2Hb) signal. Secondly, the dominant frequency of each modulation is computed using the fast Fourier transform. Finally, dominant frequencies of all modulations are fused, based on averaging, to estimate RR. The performance of the proposed method was validated on 22 young healthy subjects, whose respiratory and fNIRS signals were simultaneously recorded during a bicycling task, and compared against a zero delay Fourier domain band-pass filter. RESULTS The comparison between results obtained by the proposed method and band-pass filtering indicated the superiority of the former, with a lower mean absolute error (3.66 vs. 11.06 breaths per minute, p<0.05). The proposed fusion strategy also outperformed RR estimations based on the analysis of individual modulation. SIGNIFICANCE This study orients towards the practical limitations of traditional bio-signals for RR estimation during physical activities.
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Affiliation(s)
- Mohammad Shahbakhti
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Biomedical Engineering Institute, Kaunas University of Technology, K. Barsausko 59, LT-51423 Kaunas, Lithuania
| | - Naser Hakimi
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Department of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands
| | - Jörn M. Horschig
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
| | | | - Jurgen Claassen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Houtlaan 4, 6525 XZ Nijmegen, The Netherlands
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Phillips V Z, Canoy RJ, Paik SH, Lee SH, Kim BM. Functional Near-Infrared Spectroscopy as a Personalized Digital Healthcare Tool for Brain Monitoring. J Clin Neurol 2023; 19:115-124. [PMID: 36854332 PMCID: PMC9982178 DOI: 10.3988/jcn.2022.0406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 11/17/2022] [Accepted: 11/18/2022] [Indexed: 03/02/2023] Open
Abstract
The sustained growth of digital healthcare in the field of neurology relies on portable and cost-effective brain monitoring tools that can accurately monitor brain function in real time. Functional near-infrared spectroscopy (fNIRS) is one such tool that has become popular among researchers and clinicians as a practical alternative to functional magnetic resonance imaging, and as a complementary tool to modalities such as electroencephalography. This review covers the contribution of fNIRS to the personalized goals of digital healthcare in neurology by identifying two major trends that drive current fNIRS research. The first major trend is multimodal monitoring using fNIRS, which allows clinicians to access more data that will help them to understand the interconnection between the cerebral hemodynamics and other physiological phenomena in patients. This allows clinicians to make an overall assessment of physical health to obtain a more-detailed and individualized diagnosis. The second major trend is that fNIRS research is being conducted with naturalistic experimental paradigms that involve multisensory stimulation in familiar settings. Cerebral monitoring of multisensory stimulation during dynamic activities or within virtual reality helps to understand the complex brain activities that occur in everyday life. Finally, the scope of future fNIRS studies is discussed to facilitate more-accurate assessments of brain activation and the wider clinical acceptance of fNIRS as a medical device for digital healthcare.
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Affiliation(s)
- Zephaniah Phillips V
- Global Health Technology Research Center, College of Health Science, Korea University, Seoul, Korea.
| | - Raymart Jay Canoy
- Program in Biomicro System Technology, College of Engineering, Korea University, Seoul, Korea
| | - Seung-ho Paik
- Global Health Technology Research Center, College of Health Science, Korea University, Seoul, Korea.,KLIEN Inc., Seoul Biohub, Seoul, Korea
| | - Seung Hyun Lee
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, Korea
| | - Beop-Min Kim
- Department of Bio-Convergence Engineering, Korea University, Seoul, Korea
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Hakimi N, Shahbakhti M, Sappia S, Horschig JM, Bronkhorst M, Floor-Westerdijk M, Valenza G, Dudink J, Colier WNJM. Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference. Biosensors (Basel) 2022; 12:bios12121170. [PMID: 36551137 PMCID: PMC9775029 DOI: 10.3390/bios12121170] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/05/2022] [Accepted: 12/08/2022] [Indexed: 05/27/2023]
Abstract
OBJECTIVE Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration (O2Hb) signal are related to RR. METHODS fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best O2Hb signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered O2Hb signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing. RESULTS The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS. SIGNIFICANCE This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS.
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Affiliation(s)
- Naser Hakimi
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Department of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands
| | - Mohammad Shahbakhti
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Biomedical Engineering Institute, Kaunas University of Technology, K. Barsausko 59, LT-51423 Kaunas, Lithuania
| | - Sofia Sappia
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
| | - Jörn M. Horschig
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
| | - Mathijs Bronkhorst
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
| | | | - Gaetano Valenza
- Bioengineering and Robotics Research Center E. Piaggio and the Department of Information Engineering, School of Engineering, University of Pisa, Via G. Caruso 16, 56122 Pisa, Italy
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands
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Joshi S, Weedon BD, Esser P, Liu YC, Springett DN, Meaney A, Inacio M, Delextrat A, Kemp S, Ward T, Izadi H, Dawes H, Ayaz H. Neuroergonomic assessment of developmental coordination disorder. Sci Rep 2022; 12:10239. [PMID: 35715433 PMCID: PMC9206023 DOI: 10.1038/s41598-022-13966-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 05/31/2022] [Indexed: 12/29/2022] Open
Abstract
Until recently, neural assessments of gross motor coordination could not reliably handle active tasks, particularly in realistic environments, and offered a narrow understanding of motor-cognition. By applying a comprehensive neuroergonomic approach using optical mobile neuroimaging, we probed the neural correlates of motor functioning in young people with Developmental Coordination Disorder (DCD), a motor-learning deficit affecting 5-6% of children with lifelong complications. Neural recordings using fNIRS were collected during active ambulatory behavioral task execution from 37 Typically Developed and 48 DCD Children who performed cognitive and physical tasks in both single and dual conditions. This is the first of its kind study targeting regions of prefrontal cortical dysfunction for identification of neuropathophysiology for DCD during realistic motor tasks and is one of the largest neuroimaging study (across all modalities) involving DCD. We demonstrated that DCD is a motor-cognitive disability, as gross motor /complex tasks revealed neuro-hemodynamic deficits and dysfunction within the right middle and superior frontal gyri of the prefrontal cortex through functional near infrared spectroscopy. Furthermore, by incorporating behavioral performance, decreased neural efficiency in these regions were revealed in children with DCD, specifically during motor tasks. Lastly, we provide a framework, evaluating disorder impact in ecologically valid contexts to identify when and for whom interventional approaches are most needed and open the door for precision therapies.
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Affiliation(s)
- Shawn Joshi
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA. .,College of Medicine, Drexel University, Philadelphia, PA, USA. .,Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK. .,Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK.
| | - Benjamin D Weedon
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK
| | - Patrick Esser
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK
| | - Yan-Ci Liu
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK.,School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.,Physical Therapy Center, National Taiwan University Hospita, Taipei, Taiwan
| | - Daniella N Springett
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK.,Department for Health, University of Bath, Bath, UK
| | - Andy Meaney
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Mario Inacio
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK.,Research Center in Sports Sciences, Health Sciences and Human Development, University of Maia, Porto, Portugal
| | - Anne Delextrat
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK
| | - Steve Kemp
- Centre for Movement, Occupation and Rehabilitation Services, Oxford Brookes University, Oxford, UK
| | - Tomás Ward
- Insight SFI Research Centre for Data Analytics, Dublin City University, Dublin, Ireland
| | - Hooshang Izadi
- School of Engineering, Computing and Mathematics, School of Technology, Design and Environment, Oxford Brookes University, Oxford, UK
| | - Helen Dawes
- Nuffield Department of Clinical Neurology, University of Oxford, Oxford, UK.,Intersect@Exeter, College of Medicine and Health, University of Exeter, Exeter, UK.,Oxford Health BRC, University of Oxford, Oxford, UK
| | - Hasan Ayaz
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA.,Department of Psychological and Brain Sciences, College of Arts and Sciences, Drexel University, Philadelphia, PA, USA.,Drexel Solution Institute, Drexel University, Philadelphia, PA, USA.,Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, USA.,Center for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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