Shimmer Sensing is a leading provider of wearable sensing technology solutions and consultancy services since 2008. They offer their products and services to the research and education; pharmaceutical; enterprise; and end-user markets.
Shimmer Sensing is a leading provider of wearable sensing technology solutions and consultancy services since 2008. They offer their products and services to the research and education; pharmaceutical; enterprise; and end-user markets.
Team composition
12 members
Client name
Shimmer Sensing
Expertise used
Duration
Ongoing
Services provided
Custom software development, Data migration services, Mobile app development
Country
Ireland
Industry
Understanding that Clinical Trials are facing crisis and old objective measures are irrelevant today, our client’s goal was to meet the growing demand for medical-grade wearables. These next-generation devices are a low-cost technology that allows effective processing of real-world data for generating clinical evidence in the healthcare industry. The new solution had to provide access to sponsor and participant data to objectively measure activity and sleep indicators.
The solution was supposed to gather biometric data with the minimum technical burden on patients and clinical trial sites. It had to capture data from wrist sensors and send it to the cloud providing input data for analysis. We had to ensure data integrity and security by embedding the client’s R/Python algorithms running on AWS Lambda.
We have built a cloud-based platform and a mobile app serving as a base station and allowing for continuous patient monitoring. To meet complex data flows, we adjusted the client’s SDK logic. Our developers have embedded new code logic to meet all needed data migration requirements and developed advanced features to ensure data integrity and security.
The final solution is a combination of a fully-customizable cloud-based platform integrated with customer’s data processing algorithms and connected with sensor devices by Wi-Fi, BLE5, and LTE. The patients’ data is processed and displayed on web-based dashboards. Base stations and sensor devices can be easily configured on dashboards, as well.
Once the user is near the base station, biometric data is uploaded automatically. No actions from the patients and sponsors are needed. Due to the embedded algorithms, the data is accurate and highly-secured.
A lot of metrics can be applied and delivered to the web. The platform can process different sleep and activity data including gait parameters, joint angle calculation, Parkinson’s tremor classification, rehab exercise count, etc.
The platform is easily implemented and is fully adaptable. It can be customized to meet the specific needs of different clinical trials.
Advanced features allow for continuous remote patient monitoring. The platform can also send messages both to sites and base stations.