Identification of Respiratory Sounds Collected from Microphones Embedded in Mobile Phones

Sudden deterioration of condition in patients with various diseases, such as cardiopulmonary arrest, may result in poor outcome even after resuscitation. Early detection of deterioration is important in medical and long-term care settings, regardless of the acute or chronic phase of disease. Early detection and appropriate interventions are essential before resuscitating measures are required. Among the vital signs that indicate the general condition of a patient, respiratory rate has a greater ability to predict serious events such as thromboembolism and sepsis than heart rate and blood pressure, even in early stages. Despite its importance, however, respiratory rate is frequently overlooked and not measured, making it a neglected vital sign. To facilitate the measurement of respiratory rate, a non-invasive method of detecting respiratory sounds was developed based on deep learning technology, using a built-in microphone in a smartphone. Smartphones attached to the bed headboards of 20 participants undergoing polysomnography (PSG) at Kyoto University Hospital recorded respiratory sounds. Sound data were synchronized with overnight respiratory information. After excluding periods of abnormal breathing on the PSG report, sound data were processed for each 1-minute period. Expiration sound was determined using the pressure flow sensor signal on PSG. Finally, a model to identify the expiration section from the sound information was created using a deep learning algorithm from the convolutional Long Short Term Memory network. The accuracy of the learning model in identifying the expiratory section was 0.791, indicating that respiratory rate can be determined using the microphone in a smartphone. By collecting data from more patients and improving the accuracy of this method, respiratory rates could be more easily monitored in all situations, both inside and outside the hospital

トウカ ニオケル ラジオハ ショウシャク リョウホウ オ モチイタ カンシュヨウ チリョウ : preliminary report

Radiofrequency ablation (RFA) has recently been used to treat liver tumors. RFA is a safe and effective treatment of liver tumors and requires fewer treatment sessions. Between June 2000 and April 2003, hepatocellular carcinoma (77 patients with 106 lesions) and metastatic liver tumors (21 patients with 30 lesions) and cholangiocellular carcinoma (1 patient with 1 lesion) were treated with RFA. The liver tumors were treated percutaneously or during surgery under ultrasound guidance using a LeVeen needle (55 lesions) and cool tip RF needle (82 lesions). To evaluate the response, contrast-enhanced CT scans or MRI were obtained. Most patients experienced moderate pain during RFA procedure, especially when the tumor was superficially located. Complete necrosis was achieved in all HCCs with RFA.This result was obtained with an average of 1.12 sessions per HCC. With a median follow-up of 15 months, HCCs have recurred in 6 of 90 treated lesions (6.7%), and metastatic liver tumors have recurred in 2 of 17 treated lesions (11.8%). We are initiating a combining RFA of hepatic malignancies with regional or systemic chemotherapy will reduce hepatic and extrahepatic recurrence rates and enhance long-term survival rates. We believe that RFA will be effective treatment to achieve in patients with unresectable meastatic liver tumors

ジンソク デ アンゼンナ ジュウミン ヒナン コウドウ オ ソクシン スル ボウサイ コウドウ ケイカク ノ サクテイ

浸水被害をハード整備で防ぐには膨大な時間と経費を要するため，整備途上でも被害の最小化を図るソフト対策の充実が喫緊の課題である．本研究は2014年8月に那賀町で発生した水害時の行政と住民の対応を検証する．また，過去の那賀川における出水状況を踏まえ，はん濫発生と水位や上流のダムからの放流量の相関関係等を検証するとともに，行政が発信する災害関連情報の種類や伝達方法，住民の避難完了までに必要な時間等も検討する．その結果，住民の避難等が適正に実施されるよう，災害発生前の行政や住民の対応を時系列に沿って「いつ，だれが，何をする」を明確にした「防災行動計画」を提案する．Improvement of disaster prevention facility for a flood is necessary long time and a large amount of budget. The minimization of flood damage is incomplete without enhancement of soft measures in addition to hard measures. The serious flood damage due to Typhoon No.1411 has occurred in Naka town, Tokushima Prefecture. We analyzed the relationships between the disaster information providing by administration and evacuation of residents. Based on the results, we have developed the disaster management action plan which is called "Timeline" of government and residents