研究人員Canan Dagdeviren表示“這是第一個可以監測胃部消化情形達兩天，而無機械及電力耗損的系統。” 該裝置對於蠕動異常疾病、肥胖症的評估，服藥遵從性的監測，皆有很大的幫助。該項研究日前已發表於自然生物醫學工程期刊上。(MIT News)
MIT researchers have devised a flexible ingestible sensor that could help doctors to diagnose problems caused by a…news.mit.edu
Researchers at MIT and Brigham and Women’s Hospital develop a flexible sensor that gets into the stomach through oral ingestion; And it collects and transmits data on stomach movement and meal ingestion.
The sensor is powered by the mechanical energy generated by the stomach, and it could last for at least 48 hours to measure the movement of stomach walls; Also, researchers can have better understanding of a person’s eating, drinking and moving status by analyzing the returned data.
“This is the first system that evaluates ingestion status up to two days without any mechanical and electrical degradation” says researcher Canan Dagdeviren; The device could be helpful in the treatment of motility disorders, evaluation of obesity and the monitoring of medication adherence; The research was published in Nature Biomedical Engineering.
巴黎科技新創Cardiologs日前獲得650萬美元的融資，將用來發展人工智慧輔助心電圖分析；共同參與的投資者有Idinvest、ISAI、Kurma Partners及Partech Ventures；加上原投資者Bpifrance的種子輪資金，總募資金額已達1千萬美元。
Paris-based Cardiologs has raised $6.5 million to support its AI-powered algorithm for ECG analysis. The round was led…www.mobihealthnews.com
Paris-based Cardiologs raises $6.5 M for AI-powered ECG analysis, led by a syndicate of investors including Idinvest, ISAI, Kurma Partners, and Partech Ventures; Raises $10 M up to date.
The firm is developing a neural network, using more than 500,000 recordings, to recognize cardiac signals for analysis of heart diseases; It has both CE Mark and FDA clearance for its algorithms; And it is able to scan for 10 arrhythmias including atrial fibrillation.
Meanwhile, cardiac monitoring company iRhythm has worked with Stanford University to identify various types of arrhythmias from ECGs; Another startup Cardiogram, using the Apple Watch to monitor heart rhythm, found that the Watch could detect atrial fibrillation with 97% accuracy.