SmarKo Health® utilizes sensor-based technology and mobile applications to facilitate remote diagnosis and treatment for patients and healthcare professionals. This system addresses the challenges of timely medical assessment and intervention, enhancing patient care outside traditional clinical settings.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional methods for diagnosing and treating patients often require in-person visits, which can be inconvenient and costly, and may delay timely medical assessment and intervention, especially for those in remote areas or with mobility issues. Current fall detection systems also lack the accuracy needed to reliably predict and prevent falls in elderly populations. Furthermore, existing emergency communication systems struggle to integrate new IP-based services and technologies, limiting their effectiveness.
Solution
SmarKo Health® is a sensor-based technology and mobile application ecosystem designed to facilitate remote diagnosis and treatment, addressing the challenges of timely medical assessment and intervention outside traditional clinical settings. The SmarKo® platform utilizes a customizable sensing system suitable for various health conditions, with a focus on remote monitoring and prediction of falls in elderly people through its REPEAT project, which employs a virtual robot to simulate falls and refine monitoring algorithms. MCS Data Labs also participates in European Commission-funded projects like EMYNOS, developing next-generation emergency calling infrastructure that supports rich media, automatic location transfer, and accessibility for disabled individuals. Additionally, MCS is involved in the ONCORELIEF project, developing a guardian monitoring and decision system for post-treatment cancer patients, leveraging sensors to collect patient health data.
Target Audience
The primary target audience includes patients requiring remote monitoring and diagnosis, healthcare professionals seeking to enhance patient care outside traditional settings, elderly individuals at risk of falls, and post-treatment cancer patients needing continuous monitoring.
Features
- Customizable sensor system adaptable to various health conditions and monitoring needs.
- Mobile applications for both patients and healthcare professionals to facilitate remote interaction and data access.
- REPEAT project utilizing a virtual robot to simulate falls and improve fall detection accuracy.
- Algorithms for monitoring and predicting falls, aiming to reduce societal stress and treatment costs.
- Participation in the EMYNOS project, developing an IP-based emergency communication system.
- EMYNOS features include rich-media emergency calls, browser-based calling without plugins, and automatic caller location transfer.
- Involvement in the ONCORELIEF project, creating a guardian monitoring system for cancer patients.
- Data collection through sensors, paired with patient-provided information, to monitor post-treatment health.