2021年11月3日,

TechBullion市场充斥着自我监控衣物,但不是所有的衣物都提供相同的特性和功能。这家以色列启动Owlytics医疗和研究伙伴特拉维夫医疗中心(“Ichilov”)最近宣布第一个验证阶段的多发性硬化指标远程监控和分析解决方案,措施的有效性的药物在临床研究使用基于手机衣物和人工智能。研究利用机器学习中使用的可穿戴设备基于个人模式捕获评估慢性疾病患者如女士和帕金森氏症。机器学习功能使设备创建一个个性化的配置文件为每个病人。当设备检测到一个偏离个人模式,它为临床护理产生可行的见解,看护人,耐心。解决方案已经被制药公司利用高级生活以及家庭护理提供者在美国,英国,意大利,以色列。带来的好处是显著的,吉尔Zaphrir说,首席执行官在Owlytics,“连续室内和室外实际覆盖率减少诊所访问,减少临床研究周期。“Owlytics设备也旨在简化数据收集使用web API,从单个快照状态得分并继续详细的报告和分析工具集。“数据收集过程是自动完成的。不需要用户将表连接到一个设备如移动应用每天下载数据,“Zaphrir说。 The Owlytics analytics platform assesses multiple risk factors in the user profile, including fall risk for the elderly and the personal progression status of Parkinson’s and Multiple Sclerosis patients. The platform also includes a patient self-reporting feature. “Symptom self-reporting is considered to be of high value in preventative care today, and also enables a cognitive status assessment related to the patient’s response time,” Zaphrir explains. In addition to MS, the solution, which includes both the smartwatch wearable device, the AI-based cloud analytics, and the reporting, also supports Parkinson’s disease patients and is helpful in risk management for fraGille seniors. “Our solution is positioned to become the holy grail of common language between patients and clinicians in PD, MS, and AD diseases,” concludes Zaphrir.