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// iOS & Android Case Studies

Learn how SciChart's iOS chart library and Android chart library help 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.

Visualising Sleep and Activity Data Against Time

Read on to see how The University of Manchester Research IT’s Mobile Development Service (MDS) implemented SciChart to understand users' sleep and activity pattern in real-time.

Platform: iOS and Android

Industry: Research, Education

RAPapp is an application that allows users to send their sleep and activity data measured by their smart watches or fitness tracker to university researchers.

Challenge: To understand how the lockdown in 2020 had affected the general public and the EEA countries, the Mobile Development Service (MDS) team had challenges finding a high-performance charting tool that displays heatmaps in the exact style and speed their researchers asked for.

Solution: The MDS team used SciChart to successfully visualise about 2-years’ worth of steps sorted into 15-minute bins – around 70,000 data points. In addition to this, the integration of SciChart enabled users to view their sleep and activity heatmap in real-time – giving users insight into their daily activity during the lockdown.

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SciChart used in RAPapp
SciChart real time charting cardiac data app

Data visualization for Epilepsy Research Kit for Kids

Grand prize winner for the Microsoft annual Global Hackathon 2019

Platform: Mobile

Industry: Digital Health

MirrorHR is a mobile application, which visualizes the biometric data from a wearable device on a child or a patient who suffers from seizures. The main goal of the application is to provide realtime remote monitoring of the vital signs and trigger an alert when an anomalous activity happens. The application allows users to have a history view of a weeks' data. The history view is used to learn from data patterns and do research on the seizure’s triggers. The proof of concept of the application was created at Microsoft Hackathon 2019 and is in further development with support from FightTheStroke organization.

Challenge: to visualize the real-time data acquired from sensors with frequency starting at 1 data point every 4 seconds up to 20 data points per second for a minimum time frame of 10 hours. This is a total of 720,000 data points to be displayed. To allow displaying the history view of data, which can later be used together with AI to learn from data patterns and empower further research about the seizure triggers.

Solution: SciChart iOS library was successfully used to handle the required data rate. SciChart permitted the viewing of the biometric data coming from the wearable device on a mobile application, enabling reliable real-time remote monitoring. SciChart was also the only software in the world to handle the capacity of the history view, which was more than 1 million data points. SciChart features were utilized to add smooth interactions with the charts, including panning, zooming, drill down to a place of interest and more.

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Visualisation of Workouts Data

Discover how RepCount uses SciChart in their application, designed to improve the training experience by logging information of users’ workouts. See the solution implemented on both iOS and Android devices.

Platform: iOS and Android

Industry: Health and Fitness

RepCount is an application that gives a quick and easy way to track and analyze your gym sessions. Basic workout logging is free and unlimited; more advanced features including graphing the logged data and deep analysis of users’ results are available for the subscribers only. Charting is an essential part of the application that equips users with powerful knowledge about their workouts and brings a competitive advantage to the application.

Challenge: When looking for a charting vendor the main concern and therefore a goal was to find a solution that has not only a great performance but also active support and updates of the product.

Solution: SciChart charting was successfully implemented on both iOS and Android platforms. Supporting the latest software updates and supporting Metal for iOS platform. The performance handles the data of more than 1000 workouts sessions and is way-way far from its limits. The API was used as it is for the most charting and interactions with the charts. The customer was also able to modify the features easily to create a custom spline series of their own.

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SciChart used in Fitness App
SciChart real time charting cardiac data app

Realtime iOS Charting for Cardiac Data

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.

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Realtime Android Sensor Data Visualization on low power & cost hardware

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 class”.

Platform: Android

Industry: Engineering & Healthcare

The 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 AG 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 coming from 20 to 30 sensors, new data each 5 ms, whilst also enabling extra features such as pinch to zoom, drag/touch to pan, Axis drag and tooltips on all SciChart.Android charts.

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SciChart healthcare sensor data visualization Android Charting
SciChart real time charting trading app

High Performance iOS&Android Financial Chart Rendering

Read on to see how Broctagon Solutions incorporated SciCharts both iOS and Android Charting engine into their app to render large financial sector multi-stream Datasets in Realtime.

Platform: iOS&Android

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 mobile. 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 SciChart's Android and SciChart's iOS Chart Libraries 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.

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Realtime Waveform Visualization of Cardiovascular Data for Medical Diagnostics

Read on to see how Avicena LLC used SciChart for Android to plot in real time their multi-series Cardiovascular Data for Medical Diagnostics.

Platform: iOS

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.

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realtime high bandwidth charting ecg cardiac data scichart
SciChart real time charting big data telemetry

Realtime Android charting for Robotics Telemetry

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.

Platform: Android

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.

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Charting for Quantitative Trading Models Platform

Read on to see how Advanced Analytics Solutions, LLC launched their Brokerage app CoT Quant on Android with SciChart graphing solution.

Platform: Android (and iOS is coming next)

Industry: Financial & Trading

It is easy to get lost in the noise of financial media with conflicting and contradictory information. Advanced Analytics Solutions, LLChas launched CoT Quant app to provide investors with evidence based, data driven and clear buy or sell signals.

Challenge: To visualize realtime market data, that will assist individual traders to make intelligent buy-sell decisions. The data from advanced analytics models that are also highly complex and are constantly adapting to newly available information should be shown in an informative, easy to use and clear way.

Solution: SciChart Android Charts were implemented to Cot Quant app and provided a fast, reliable & efficient charting solution. Advanced Analytics Solutions, LLC was able to achieve handling of large complex data on multiple charts synchronised over panels while maintaining a smooth user interface with Realtime updates.

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realtime high bandwidth charting ecg cardiac data scichart

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