Cookies and the protection of your data

We use cookies to improve the functionality of the website, to offer you a better website experience and to provide social media features. You give your consent by clicking on “Accept all Cookies” or as part of your individual settings. Please find detailed information on the use of cookies on this website in our Data Privacy Statement.

Functional Cookies

These cookies are necessary for the operation of the site and enable security-relevant functions. In addition, we determine whether you want to remain logged in and to make our services available to you when you change between this and other websites.

Statistical Cookies

These cookies are used for analyzing user behavior on our website with the aim of improving user navigation. All data collected is evaluated anonymously. Further information is available on our data protection site.

Marketing Cookies

These cookies are used to deliver relevant advertising or to limit how many times you see an ad. Marketing cookies can share that information with the advertiser (third-party cookies). The legal basis for the data processing is the consent of the user.

Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
Pregnancy Risk Flagging System
2023

Share:

Pregnancy Risk Flagging System

Symptom data analysis for early risk detection

Philips

According to WHO 15% of pregnant women are estimated to develop a life-threatening complication. To avoid preventable deaths, caregivers need to detect risks and intervene as early as possible. The Pregnancy Risk Flagging System is designed for real-time identification of hidden emerging pregnancy risks. It guides pregnant women, via a user-friendly app, to accurately report any symptom or discomfort experienced between antenatal care visits. Data is then analyzed by a cloud-based algorithm that alerts caregivers to take prompt actions when risks are flagged. This early warning system can help to safe lives.

Client / Manufacturer
Philips

Philips

Eindhoven, NL
Design
Philips Experience Design Team

Philips Experience Design Team

Eindhoven, NL

Máxima Medical Center Team

Veldhoven, NL
Date of Launch
2023
Development Time
up to 12 Month
Target Regions
Europe
Target Groups
"patients and healthcare"

RELATED PROJECTS