• Journal of IKEEE
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• v.21 no.4
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• pp.397-403
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• 2017

In the modern society, psychological diseases and impulsive crimes due to stress are occurring. In order to reduce the stress, the existing treatment methods consisted of continuous visit counseling to determine the psychological state and prescribe medication or psychotherapy. Although this face-to-face counseling method is effective, it takes much time to determine the state of the patient, and there is a problem of treatment efficiency that is difficult to be continuously managed depending on the individual situation. In this paper, we propose an artificial intelligence emotion management system that emotions of user monitor in real time and induced to a table state. The system measures multiple bio-signals based on the PPG and the GSR sensors, preprocesses the data into appropriate data types, and classifies four typical emotional states such as pleasure, relax, sadness, and horror through the SVM algorithm. We verify that the emotion of the user is guided to a stable state by providing a real-time emotion management service when the classification result is judged to be a negative state such as sadness or fear through experiments.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.731-736
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• 2023

Recently, the medical field has been applying mandatory Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) systems that computerize and manage medical records, and distributing them throughout the entire medical industry to utilize patients' past medical records for additional medical procedures. However, the conversations between medical professionals and patients that occur during general medical consultations and counseling sessions are not separately recorded or stored, so additional important patient information cannot be efficiently utilized. Therefore, we propose an electronic medical record system that uses speech recognition and natural language processing deep learning to store conversations between medical professionals and patients in text form, automatically extracts and summarizes important medical consultation information, and generates electronic medical records. The system acquires text information through the recognition process of medical professionals and patients' medical consultation content. The acquired text is then divided into multiple sentences, and the importance of multiple keywords included in the generated sentences is calculated. Based on the calculated importance, the system ranks multiple sentences and summarizes them to create the final electronic medical record data. The proposed system's performance is verified to be excellent through quantitative analysis.

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.253-258
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• 2022

It is a widely known fact that MAC addresses can be collected using Wi-Fi from mobile phones that people carry. However, since collecting and using MAC addresses without individual consent entails many legal problems, it was difficult to actively utilize them. In order to prevent invasion of privacy information due to unintentional exposure of these MAC addresses in recent years, the method of protecting privacy information by exposing a randomly generated virtual MAC address rather than the MAC address of the actual device is applied to all mobile devices. is becoming By exposing a randomly generated virtual MAC address on a device, it becomes impossible to identify and track an individual using the MAC address. However, the fact that various facts can be estimated through MAC Address collection is still valid. By expanding the application of Random MAC Address, the possibility of invasion of privacy information has been completely removed from the MAC address that has been raised in the past, so that it can be used more actively than in the past. In this paper, we propose a method for automatically collecting and analyzing statistical information of hospital visitors using MAC addresses. The collection of hospital visitors using MAC Address is a low cost and relatively accurate method, and the analysis of hospital visitors through steady collection can provide very objective and scientific evidence for hospital operation.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.33-38
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• 2014

Purpose Auto exposure control (AEC) in SPECT/CT automatically controls the exposure dose (mA) according to patient's shape and size. The aim of this study was to evaluate the effect of AEC in SPECT/CT on exposure dose reduction and image quality. Materials and Methods The model of SPECT/CT used in this study was Discovery 670 (GE, USA), Smart mA for AEC; and $^{99m}Tc$ as a radioisotope. To compare SPECT and CT images by CT exposure dose variation, we used a standard technique set at 80, 100, 120, 140 kVp, 10, 30, 50, 100, 150, 200, 250 mA, and AEC at 80, 100, 120, 140 kVp, 10-250 mA. To evaluate resolution and contrast of SPECT images, triple line phantom and flangeless Esser PET phantom were used. For CT images, noise and uniformity were checked by anthropomrphic chest phantom. For dose evaluation to find DLP value, anthropomorphic chest phantom was used and the CT protocol of torso was applied by standard technique (120 kVp, 100 mA) and AEC (120 kVp, 10-250 mA). Results When standard and AEC were applied, the resolutions at SPECT images with attenuation correction (AC) were the same as FWHM by center 3.65 mm, left 3.48 mm, right 3.61 mm. Contrasts of standard and AEC showed no significant difference: standard 53.5, 29.8, 22.5, 15.8, 6.0, AEC 53.5, 29.6, 22.4, 15.7, 6.1 In CT images, noise values at standard and AEC were 15.4 and 18.5 respectively. The application of AEC increases noise but the value of coefficient variation were 33.8, 24.9 respectively, obtaining uniform noise image. The values of DLP at standard and AEC were 426.78 and 352.09 each, which shows that the application of AEC decreases exposure dose more than standard by approximately 18%. Conclusion The results of our study show that there was no difference of AC in SPECT images based on the CT exposure dose variation at SPECT/CT images. It was found that the increased CT exposure dose leads to the improvement of CT image quality but also increases the exposure dose. Thus, the use of AEC in SPECT/CT contributes to obtaining equal AC SPECT images, and uniform noise in CT images while reducing exposure dose.

• Radiation Oncology Journal
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• v.27 no.3
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• pp.120-125
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• 2009

Purpose: We wanted to present the preliminary results of intensity-modulated radiotherapy (IMRT) for the treatment of tonsillar cancer. Materials and Methods: We retrospectively analyzed 12 patients who underwent IMRT for tonsillar cancer at Asan Medical Center between November 2002 and February 2007. Seven patients (58%) received definitive treatment, and five (42%) were treated in the postoperative setting. Among the definitively treated patients, 6 patients received cisplatin-based chemotherapy regimens. Simultaneous modulated accelerated radiation therapy (SMART) was used in nine patients. The prescribed dose was 72 Gy at 2.4 Gy/fraction for the definitively treated cases and 61.6 Gy at 2.2 Gy/fraction for the postoperative cases. The median follow-up period was 34 months. Results: All twelve patients completed treatment without interruption, and eleven showed a complete response. One patient had persistent loco-regional disease after treatment. The three-year estimates of loco-regional control, disease-free survival and overall survival were 91.7%, 91.7%, and 100%. The worst acute mucositis was Grade 1 in four patients, Grade 2 in five patients, Grade 3 in two patients and Grade 4 in one patient. Grade 3 xerostomia was observed in six patients. Conclusion: Intensity-modulated radiotherapy was shown to be a safe and effective treatment modality for tonsillar cancer. Further studies with a larger number of patients and a longer follow-up period are needed to evaluate the ultimate tumor control and late toxicity of IMRT for treating tonsillar cancer.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.1
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• pp.30-35
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• 2013

Purpose: One of the current services, providing information to the patients and their guardians by using promotion materials induces positive responses and contributes to the improvement of the hospital reliability. Therefore, the objective of this study is to evaluate the effectiveness of audio visual materials, one of the means of promotion, as a way to give accurate medical information to resolve patient's curiosity about purpose and procedure of their examination and deplete complains about waiting which attributes negative effect to service quality assessment. Materials and Methods: 60 patients(mean age $53.97{\pm}12.24$, male : female = 26 : 34) who had $^{18}F-FDG PET/CT$ scan from July 2012 to August 2012 in Seoul Asan Medical Center were referred to the study. All of the patients having PET/CT scan were asked to watch an informative video material before the injection of radiopharmaceutical ($^{18}F-FDG$) and to fill in a questionnaire. Results: As a result of analyzing the contents of questionnaire, 52% of 60 patients had PET/CT scan for the first time and 72.4% of the patients read the PET/CT guidebook offered from their outpatient department or inpatient wards before their scan. After we searched the level of previous knowledge of the purpose and method of PET/CT scan, the patients answered 25.1% "know well", 34% "not sure", 40.9% "don't know" respectively. And 84.7% of the patients answered that watching the PET/CT guide video before the injection helps understanding what exam they were having and 15.3% of the patients did not. For the question asking ever the patients have experienced using our homepage or smart phone QR code to see the guide video before they visit out PET center, only 3.3% of them answered "yes". Lastly, the patients answered 60.1% "yes", 31.4% "so so" and 8.5% "no" respectively for the question asking whether watching the video makes the patients to fill the waiting time short. Conclusion: It is found that understanding of objective and method of the PET/CT scan and level of satisfaction was improved after the patients watched the guide video whether they had PET/CT scan before and read the PET/CT guidebook or not. Also, watching the video was effective for the reduction of perceptible waiting time. But while displaying the PET/CT guide video is useful for providing information about the scan and shortening the waiting time as one of the medical service, utilization of service was actually very poor because of the passive promotion and indifference of the patients about their examination. Therefore, from now on, it is necessary to construct the healthcare system which can be offered to more patients through the active promotion.

• Phonetics and Speech Sciences
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• v.11 no.1
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• pp.51-61
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• 2019

The purpose of this study was to develop a smartphone based voice therapy program for patients with voice disorders. Contents of voice therapy were collected through analysis of mobile contents related to voice therapy in Korea, experts and users' demand survey, and the program was developed using Android Studio. Content needed for voice therapy was collected through analysis of mobile contents related to voice therapy. The user satisfaction evaluation for application was conducted for five patient with functional voice disorders. The results showed that the mobile contents related to voice therapy in Korea were mostly related to breathing, followed by voice and singing, but only 13 applications were practically practiced for voice therapy. Expert and user demand surveys showed that the patients and therapists both had a high need for content that could provide voice training in places other than the treatment room. Based on this analysis, 'Home Voice Trainer', an smartphone based voice therapy program, was developed. Home Voice Trainer is an application for voice therapy and management based on Android smartphones. It is designed to train voice therapy activities at home that have been trained offline. In addition, the records of voice training of patients were managed online so that patients can maintain voice improvement through continuous voice consulting even after the end of voice therapy. User evaluations show that patients are satisfied with the difficulty and content of voice therapy programs provided by home voice trainers, but lack of a portion of user interface, such as the portion of home button and interface between screens. Further study suggests the clinical application of home voice trainer to the patients with voice disorders. It is expected that the development study and the clinical application of smart contents related to voice therapy will be actively conducted.