SciChart® the market leader in Fast WPF Charts, WPF 3D Charts, and now iOS Charting & Android Chart Components
Learn how SciChart helps our customers with data visualisation in their Projects. Through a combination of Speed, Performance & Flexibility we are able to make even impossible tasks possible. We’ve helped many companies and individuals to make their projects a reality. Read on to see what SciChart could do for your project.
Read on to see how iHealth Technologies Ltd built a health & fitness app using SciChart on iPhone & iPad to display accurate Realtime iOS charts for large amounts of data points derived from Polarsec and MyZone Heart rate monitors.
Platform: iOS (iPhone, iPad, iWatch)
Industry: Health & Fitness
iHealth’s vision was to create a fitness app that would be taken seriously. Something that was considered a real training tool, that offered measurable improvements by tracking heart rate data, %VO2 max and physiological stress levels backed by Biometric driven software giving each user adaptive and individualised targets.
Challenge: To display 70,000 points of heart rate data accurately and in Realtime. Data is recorded live during custom training sessions to show the calculated “effort” index and true heart rate trends in a custom line and bar chart whilst maintaining a smooth UI across platforms.
Solution: Custom iOS charts were integrated into the iHealth app complying with existing styling. Namely custom bar and line charts that could handle the data sets, visualize live heart-rate data and maintain a smooth, rich touch interaction with added panning, pinch to zoom, drag and tooltips functionality.
Read on to see how IMT AG adopted SciChart for Android to run on their low power & cost hardware testing device for the medical indisrty the Citrex H5 voted “The best mobile test device in its call”.
Industry: Engineering & Healthcare
IMT’s Citrex H5 project was built as a testing device for medical industry, that measures the performance of breathing ventilators. Described as a “Gas Flow Analyzer”, the Citrex H5 was designed as an all-in-one testing device for biomedical technicians, independent service organisations and anaesthesia device and ventilation manufacturers.
Challenge: To retain a smooth Realtime line and mountain chart depiction on a custom testing device for medical industry and embedded system with very low power and cost hardware. Limited to a Dual core A9 CPU at under 800Mhz and only 1GB RAM running Android Lollipop 5.1.1 previous in house charting solutions couldn’t function.
Solution: Android charts by SciChart were designed in collaboration with IMT to function with their bespoke hardware limitations creating an extremely lean & efficient software package. SciChart’s High Performance capabilities were used to handle the data sets at 30FPS on only 400Mhz whilst also enabling extra features such as pinch to zoom, drag/touch to pan, Axis drag and tooltips on all SciChart.Android charts.
Read on to see how Broctagon Solutions incorporated SciCharts Android Charting engine into their app to render large financial sector multi-stream Datasets in Realtime.
Industry: Financial, Trading
Broctagon Solutions, founded on the belief that the derivatives industry was in an evident need of a better derivatives trading platform needed a Charting component that could handle complicated financial data sets in real time on Android. Set on ensuring the best end user experience, Broctagon needed a charting solution that was capable of extreme performance and packed extra features for increased functionality whilst looking slick and remaining easy to use.
Challenge:To render in real time the large multi-stream datasets inherent to the financial and trading sectors. Outputting in several different charting styles such as OHLC and Candlesticks alongside overlaid annotations, tooltips and multiple panes without sacrificing smoothness and increasing the end user experience.
Solution: Broctagon utilised SciCharts Android Chart Library to render large data sets whilst maintaining increased performance and speed in Realtime. Extensive theming and customisation options allowed the support of multiple axis and coordinates whilst improving end user experience with added functionality such as panning, scrolling and series selection.
Read on to see how Avicena LLC used SciChart for Android to plot in real time their multi-series Cardiovascular Data for Medical Diagnostics.
Industry: Scientific & Medical Diagnostics
Avicena is a medical device company focused on providing critical information to patients and physicians through their mobile app which works in conjunction with their bespoke proprietary sensor platform the Vivio. The Vivio streams live cardiovascular data directly to a mobile device via Bluetooth to aid in Cardiovascular diagnosis.
Challenge: To display accurate Realtime, High-Bandwidth Cardiovascular data in up to 90 series streamed from their sensor device whilst maintaining a smooth UI and allowing for bespoke customizations and annotations.
Solution: Avicena used SciChart’s exceptional performance to render over a million data points at interactive frame rates whilst handling 90 series simultaneously. They utilised the extensive charting library to display data in in Lines, Bands and ECGs whilst creating a fully customized UI using our Rich Chart Annotations API.
Read on to see how MIT Biomimetic Robotics Lab used SciChart for Android to display and interpret Realtime telemetry data from Smart shoe sensors designed to capture measurements of force-data during movement.
Industry: Robotics, Biomimetics
Organic organisms contain an abundance of surface skin sensors that can determine pressure, vibrations and forces which in turn feedback and allow calibration of movement. The Biomimetic Robotics lab at MIT aimed to develop a similar multi-axis force sensor for use in the next generation of legged robots by mapping the local sampling of stress inside their custom polymeric footpad. Their goal is to use these force sensing shoes to help assist the elderly and disabled during walking for fall prevention and mitigation as well as to provide athletes with training data.
Challenge: To visualize multiple streams of data at 1kHz amounting to hundreds of thousands of data points collected from smart shoe telemetry on an Android app. Open source solution had been unable to handle the sensor output and match the performance requirements.
Solution: SciChart’s Android charts were integrated by MIT into their own app for reading and visualising telemetry data. SciChart’s big data capabilities were used to plot the huge amounts of data output by their custom sensors and were displayed smoothly by SciCharts Android Realtime charting engine whilst enabling smooth rich touch interaction functionality.