Visual Analysis for Application of Functional Near-Infrared Spectroscopy in Rehabilitation Medicine Field over the Past Decade

LI Sihui, LENG Jun, CHEN Yiting, YANG Rong, LIANG Chunting, CHENG Xiaofei

China Medical Devices ›› 2025, Vol. 40 ›› Issue (3) : 126-133.

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China Medical Devices ›› 2025, Vol. 40 ›› Issue (3) : 126-133. DOI: 10.3969/j.issn.1674-1633.20241250
RESEARCHWORK

Visual Analysis for Application of Functional Near-Infrared Spectroscopy in Rehabilitation Medicine Field over the Past Decade

  • LI Sihui1, LENG Jun2, CHEN Yiting3, YANG Rong1, LIANG Chunting1, CHENG Xiaofei1
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Abstract

ObjectiveTo analyze the current situation, hotspot and evolution trend of functional near-infrared spectroscopy (fNIRS) in the field of rehabilitation medicine over the past decade. Methods Literature related to the application of fNIRS technology in the field of rehabilitation medicine from January 2013 to June 2024 were retrieved from Web of Science, and visual analysis was performed by CiteSpace 6.3.R1 software. Results A total of 1036 literatures were finally included, and the number of published literatures showed an increasing trend year by year. LI Zengyong was the most prolific author in this field. China was the country with the highest number of articles. Beihang University was the most prolific institution. Research focused on cortical activation, stroke, functional connectivity, transcranial magnetic stimulation, neuroimaging, motor imagery, brain-computer interface and cognitive impairment. Conclusion The application of fNIRS technology in the field of rehabilitation medicine is in the development stage, and domestic institutions should strengthen cooperation and exchanges. In recent years, research in this field has begun to integrate multimodal monitoring of brain activation and connection-related features to learn more about motor behavior and neurophysiological mechanisms. In the future, we will continue to focus on the application of fNIRS technology in patients with stroke, spinal cord injury, Parkinson’s disease and Alzheimer’s disease.

Key words

functional near-infrared spectroscopy (fNIRS); stroke rehabilitation; functional connection; disturbance of consciousness; functional brain imaging; brain-computer interface; CiteSpace; visual analysis

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LI Sihui, LENG Jun, CHEN Yiting, et al. Visual Analysis for Application of Functional Near-Infrared Spectroscopy in Rehabilitation Medicine Field over the Past Decade[J]. China Medical Devices, 2025, 40(3): 126-133 https://doi.org/10.3969/j.issn.1674-1633.20241250

References

[1] Tian TS. Functional data analysis in brain imaging studies[J]. Front Psychol, 2010, 1: 35.
[2] 钱志余, 李韪韬. 功能近红外光谱技术(fNIRs)临床应用综述[J]. 生命科学仪器, 2013, 11(3): 45-52.
Qian ZY, Li WT. Functional near-infrared spectroscopy (fNIRs) clinical applications review[J]. Life Sci Instrum, 2013, 11(3): 45-52.
[3] Raichle ME. Functional brain imaging and human brain function[J]. J Neurosci, 2003, 23(10): 3959-3962.
[4] Boas DA, Elwell CE, Ferrari M, et al. Twenty years of functional near-infrared spectroscopy: introduction for the special issue[J]. Neuroimage, 2014, 85 Pt 1: 1-5.
[5] Ferrari M, Quaresima V. A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application[J]. Neuroimage, 2012, 63(2): 921-935.
[6] Crosson B, Ford A, McGregor KM, et al. Functional imaging and related techniques: an introduction for rehabilitation researchers[J]. J Rehabil Res Dev, 2010, 47(2): vii-xxxiv.
[7] 吴毅. 功能性近红外光谱技术在脑卒中患者康复中的临床应 用[J]. 中国康复医学杂志, 2020, 35(11): 1281-1283.
[8] Bai Z, Fong KNK. “Remind-to-Move” treatment enhanced activation of the primary motor cortex in patients with stroke[J]. Brain Topogr, 2020, 33(2): 275-283.
[9] Bai Z, Fong KNK, Zhang J, et al. Cortical mapping of mirror visual feedback training for unilateral upper extremity: a functional near-infrared spectroscopy study[J]. Brain Behav, 2020, 10(1): e01489.
[10] Huo C, Sun Z, Xu G, et al. fNIRS-based brain functional response to robot-assisted training for upper-limb in stroke patients with hemiplegia[J]. Front Aging Neurosci, 2022, 14: 1060734.
[11] Liu Z, Zhang M, Xu G, et al. Effective connectivity analysis of the brain network in drivers during actual driving using nearinfrared spectroscopy[J]. Front Behav Neurosci, 2017, 11: 211.
[12] Li Z, Zhang M, Xin Q, et al. Spectral analysis of near-infrared spectroscopy signals measured from prefrontal lobe in subjects at risk for stroke[J]. Med Phys, 2012, 39(4): 2179-2185.
[13] Lu K, Xu G, Li W, et al. Frequency-specific functional connectivity related to the rehabilitation task of stroke patients[J]. Med Phys, 2019, 46(4): 1545-1560.
[14] Chen YH, Sawan M. Trends and challenges of wearable multimodal technologies for stroke risk prediction[J]. Sensors (Basel), 2021, 21(2): 460.
[15] Xu G, Huo C, Yin J, et al. Effective brain network analysis in unilateral and bilateral upper limb exercise training in subjects with stroke[J]. Med Phys, 2022, 49(5): 3333-3346.
[16] Huo C, Xu G, Xie H, et al. Effect of high-frequency rTMS combined with bilateral arm training on brain functional network in patients with chronic stroke: an fNIRS study[J]. Brain Res, 2023, 1809: 148357.
[17] Chen C. Predictive effects of structural variation on citation counts[J]. J Assoc Inf Sci Technol, 2012, 63(3): 431-449.
[18] Yang M, Yang Z, Yuan T, et al. A systemic review of functional near-infrared spectroscopy for stroke: current application and future directions[J]. Front Neurol, 2019, 10: 58.
[19] 近红外脑功能成像临床应用专家共识编写组. 近红外脑 功能成像临床应用专家共识[J]. 中国老年保健医学, 2021, 19(2): 3-9.
Expert consensus on clinical application of near-infrared brain functional imaging technology writing group. Expert consensus on clinical application of near-infrared brain functional imaging technology[J]. Chin J Geriatr Care, 2021, 19(2): 3-9.
[20] 刘俊明, 方蕊, 杨伟伟, 等. 中等强度运动对健康女青年智力 的影响——一项基于近红外光谱的研究 [J]. 中国康复, 2023, 38(6): 340-344.
Liu JM, Fang R, Yang WW, et al. Effect of moderate intensity exercise on intelligence of healthy young women: a study based on functional near-infrared spectroscopy[J]. Chin J Rehabil, 2023, 38(6): 340-344.
[21] Baker JM, Bruno JL, Gundran A, et al. fNIRS measurement of cortical activation and functional connectivity during a visuospatial working memory task[J]. PLoS One, 2018, 13(8): e0201486.
[22] Yang CL, Lim SB, Peters S, et al. Cortical activation during shoulder and finger movements in healthy adults: a functional near-infrared spectroscopy (fNIRS) study[J]. Front Hum Neurosci, 2020, 14: 260.
[23] Huo C, Xu G, Li Z, et al. Limb linkage rehabilitation trainingrelated changes in cortical activation and effective connectivity after stroke: a functional near-infrared spectroscopy study[J]. Sci Rep, 2019, 9(1): 6226.
[24] Yücel MA, Lühmann AV, Scholkmann F, et al. Best practices for fNIRS publications[J]. Neurophotonics, 2021, 8(1): 012101.
[25] Pinti P, Tachtsidis I, Hamilton A, et al. The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience[J]. Ann N Y Acad Sci, 2020, 1464(1): 5-29.
[26] Chen WL, Wagner J, Heugel N, et al. Functional nearinfrared spectroscopy and its clinical application in the field of neuroscience: advances and future directions[J]. Front Neurosci, 2020, 14: 724.
[27] Vijayakrishnan Nair V, Kish BR, Yang HS, et al. Monitoring anesthesia using simultaneous functional near infrared spectroscopy and electroencephalography[J]. Clin Neurophysiol, 2021, 132(7): 1636-1646.
[28] Yang J, Ji X, Quan W, et al. Classification of schizophrenia by functional connectivity strength using functional near infrared spectroscopy[J]. Front Neuroinform, 2020, 14: 40.
[29] Scholkmann F, Tachtsidis I, Wolf M, et al. Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain[J]. Neurophotonics, 2022, 9(3): 030801.
[30] Liu Z, Yin Y, Liu W, et al. Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis[J]. Scientometrics, 2015, 103: 135-158.
[31] Chen C, Ibekwe-Sanjuan F, Hou J. The structure and dynamics of co-citation clusters: a multiple-perspective co-citation analysis[J]. J Am Soc Inf Sci Technol, 2014, 61(7): 1386-1409.
[32] Poo MM, Du JL, Ip NY, et al. China brain project: basic neuroscience, brain diseases, and brain-inspired computing[J]. Neuron, 2016, 92(3): 591-596.
[33] 孙维震, 孙志芳, 罗美玲, 等. 平板步行训练中帕金森病患者 脑网络的功能性近红外光谱技术研究[J]. 中国康复医学杂 志, 2023, 38(6): 742-748.
Sun WZ, Sun ZF, Luo ML, et al. Brain network analysis during treadmill training in patients with Parkinson’s disease: an fNIRS study[J]. Chin J Rehabil Med, 2023, 38(6): 742-748.
[34] 徐功铖, 霍聪聪, 李文昊, 等. 基于功能性近红外光谱的脑卒 中后偏侧与双侧运动训练对脑功能的影响分析[J]. 医用生物 力学, 2019(s1): 171-172.
[35] Chen C. Searching for intellectual turning points: progressive knowledge domain visualization[J]. Proc Natl Acad Sci U S A, 2004, 101 Suppl 1(Suppl 1): 5303-5310.
[36] Liu N, Yücel MA, Tong Y, et al. Editorial: fNIRS in neuroscience and its emerging applications[J]. Front Neurosci, 2022, 16: 960591.
[37] Chen J, Xia Y, Zhou X, et al. fNIRS-EEG BCIs for motor rehabilitation: a review[J]. Bioengineering (Basel), 2023, 10(12): 1393.
[38] Delorme M, Vergotte G, Perrey S, et al. Time course of sensorimotor cortex reorganization during upper extremity task accompanying motor recovery early after stroke: an fNIRS study[J]. Restor Neurol Neurosci, 2019, 37(3): 207-218.
[39] Bhattacharjee S, Kashyap R, Abualait T, et al. The role of primary motor cortex: more than movement execution[J]. J Mot Behav, 2021, 53(2): 258-274.
[40] 金涛, 李浩正, 鲍春蓉, 等. 脑卒中后认知功能障碍患者的功能 性近红外脑网络特征分析[J]. 康复学报, 2024, 34(4): 341-348.
Jin T, Li HZ, Bao CR, et al. Functional near-infrared brain network characteristics analysis in patients with cognitive impairment after stroke[J]. Rehabil Med, 2024, 34(4): 341-348.
[41] Kalra L, Dobkin BH. Facilitating mental imagery to improve mobility after stroke: all in the head[J]. Neurology, 2021, 96(21): 975-976.
[42] 周静, 杨远滨, 田浩林, 等. 基于近红外脑功能成像技术指导 下运动想象训练在脑卒中后上肢运动功能康复中的应用[J]. 中国康复, 2024, 39(3): 131-134.
Zhou J, Yang YB, Tian HL, et al. Application of mental imagery based on fNIRS in rehabilitation of stroke patients with upper limb paralysis[J]. Chin J Rehabil, 2024, 39(3): 131-134.
[43] Sun X, Long H, Zhao C, et al. Analgesia-enhancing effects of repetitive transcranial magnetic stimulation on neuropathic pain after spinal cord injury: an fNIRS study[J]. Restor Neurol Neurosci, 2019, 37(5): 497-507.
[44] 石曼欣妤, 孟德涛, 方伯言. 帕金森病康复研究进展的可视 化分析[J]. 中国康复理论与实践, 2022, 28(9): 1060-1064.
Shi MXY, Meng DT, Fang BY. Advance in Parkinson’s disease rehabilitation: a visualization analysis[J]. Chin J Rehabil Theory Pract, 2022, 28(9): 1060-1064.
[45] 琚芬, 赵晨光, 袁华, 等. 脑机接口在康复医学中的应用进展[J]. 中国康复, 2017, 32(6): 508-511.
[46] Borgheai SB, McLinden J, Zisk AH, et al. Enhancing communication for people in late-stage ALS using an fNIRSbased BCI system[J]. IEEE Trans Neural Syst Rehabil Eng, 2020, 28(5): 1198-1207.
[47] Herold F, Wiegel P, Scholkmann F, et al. Applications of functional near-infrared spectroscopy (fNIRS) neuroimaging in exercise-cognition science: a systematic, methodology-focused review[J]. J Clin Med, 2018, 7(12): 466.
[48] Wang Z, Ren K, Li D, et al. Assessment of brain function in patients with cognitive impairment based on fNIRS and gait analysis[J]. Front Aging Neurosci, 2022, 14: 799732.
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