Dynamic Quantification of Migrainous Thermal Facial Patterns – A Pilot Study

Pavlidis, Ioannis; Garza, Ivan; Tsiamyrtzis, Panagiotis; Dcosta, Malcolm; Swanson, Jerry W.; Krouskop, Thomas A.; Levine, James A.

doi:10.1109/jbhi.2018.2855670

Cited by 5 publications

(2 citation statements)

References 27 publications

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“…Further, assessing the effects of a novel method like rPMS on advanced migraine markers evaluated by emerging technologies, i.e. the expression of specific neurosteroid www.nature.com/scientificreports www.nature.com/scientificreports/ patterns or facial electronic thermography, may track progress in the understanding of distinct neuromodulatory mechanisms [56][57][58][59][60] .…”

Section: Discussionmentioning

confidence: 99%

Alleviation of migraine symptoms by application of repetitive peripheral magnetic stimulation to myofascial trigger points of neck and shoulder muscles – A randomized trial

Renner

Sollmann

Heinen

et al. 2020

Sci Rep

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Migraine is a burdensome disease with an especially high prevalence in women between the age of 15 and 49 years. Non-pharmacological, non-invasive therapeutic methods to control symptoms are increasingly in demand to complement a multimodal intervention approach in migraine. Thirty-seven subjects (age: 25.0 ± 4.1 years; 36 females) diagnosed with high-frequency episodic migraine who presented at least one active myofascial trigger point (mTrP) in the trapezius muscles and at least one latent mTrP in the deltoid muscles bilaterally prospectively underwent six sessions of repetitive peripheral magnetic stimulation (rPMS) over two weeks. Patients were randomly assigned to receive rPMS applied to the mTrPs of the trapezius (n = 19) or deltoid muscles (n = 18). Whereas the trapezius muscle is supposed to be part of the trigemino-cervical complex (TCC) and, thus, involved in the pathophysiology of migraine, the deltoid muscle was not expected to interfere with the TCC and was therefore chosen as a control stimulation site. The headache calendar of the German Migraine and Headache Society (DMKG) as well as the Migraine Disability Assessment (MIDAS) questionnaire were used to evaluate stimulation-related effects. Frequency of headache days decreased significantly in both the trapezius and the deltoid group after six sessions of rPMS (trapezius group: p = 0.005; deltoid group: p = 0.003). The MIDAS score decreased significantly from 29 to 13 points (p = 0.0004) in the trapezius and from 31 to 15 points (p = 0.002) in the deltoid group. Thus, rPMS applied to mTrPs of neck and shoulder muscles offers a promising approach to alleviate headache frequency and symptom burden. Future clinical trials are needed to examine more profoundly these effects, preferably using a sham-controlled setting. According to the Global Burden of Disease Study more than one billion people were suffering from migraine in 2016, making migraine one of the most prevalent neurological disorders worldwide 1. Especially women between the age of 15 and 49 years are concerned-in this group migraine is also the first cause of disability worldwide 1-4. Further, migraineurs show a considerably reduced health-related quality of life (QoL) and considerable loss in work productivity 5-7. The high impact of migraine on QoL is reflected by percentages as high as 85%

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Section: Discussionmentioning

confidence: 99%

Alleviation of migraine symptoms by application of repetitive peripheral magnetic stimulation to myofascial trigger points of neck and shoulder muscles – A randomized trial

Renner

Sollmann

Heinen

et al. 2020

Sci Rep

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“…Many studies in the past 20 years have used infrared thermal imaging to recognize fear and anxiety among emotions [16][17][18][19][20][21][22][23][24]. Face imaging signals have likewise been applied to extract relevant physiological information, and these signals also play an important role in emotion recognition.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial–Spectral–Temporal Framework for Emotion Recognition

Hong

2020

IEEE Access

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An emotion recognition method based on multispectral imaging technology and tissue oxygen saturation (StO2) is proposed in this study. This method is called spatial-spectral-temporal adjustment convolutional neural network (SACNN). First, we use the algorithm to extract the StO2 content of an emotionally sensitive nose area through real-time multispectral imaging technology. Compared with facial expression data, StO2 data are more objective and cannot be controlled and changed artificially. Second, we construct a clustering algorithm based on the emotional state by extracting the spectral, StO2, and spatial features of the nose image to obtain accurate signals of emotionally sensitive areas. To utilize the correlation between spectral and spatial signals, we propose an adjustment-based CNN module, which reorganizes the relationship between all previous layers of the feature map, thereby making the relationship among layers close and highly quantitative. The features extracted through this method are consistent with spatial-spectral features. Third, we incorporate the extracted temporal feature signal into the long short-term memory module and finally complete the correlation between the spatial-spectral-temporal features. Experimental results show that the accuracy of the SACNN algorithm in emotional recognition reaches 90%, and the proposed method is more competitive than state-of-the-art approaches. To the best of our knowledge, this study is the first to use time-series StO2 signals for emotion recognition. INDEX TERMS Multispectral imaging, oxygen saturation, spatial-spectral-temporal adjustment convolutional neural network. I.

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