With our OpenSignals software you can do live data visualization and recording on Windows, Linux, Mac OS and Android. Software modules are provided as open source code by our user base that enable you to easily perform signal processing, feature extraction and other useful tasks. Professional Data Visualization Software to Visualize Data Effortlessly Creating charts and infographics can be time-consuming. But the right tool makes it easier. Edraw is the optimal tool to create stunning visualizations with ease.
OpenSignals (r)evolution
Check out the fact sheet... this is our easy-to-use, versatile, and scalable software for real-time biosignals visualization, capable of direct interaction with BITalino. Core functionality includes sensor data acquisition from multiple channels and devices, data visualization and recording, as well as loading of pre-recorded signals.
Data processing modules are available as optional add-ons, enabling one to do Heart Rate Variability (HRV) analysis, extraction of statistical indicators from EMG data, and other convenient operations. OpenSignals is also a Python-powered web-based software framework, targeted at rapid application development; a bare bone code base is available on our GitHub.
Documentation
The user manual for OpenSignals (r)evolution (v.2019) is available here
Mac Os X Data Visualization Software Free
Latest version available: September 02 2019 (win/mac)
EXE | ZIP
Win 64-bit (v.2020)
EXE | ZIP
Previous version available: | ||
| Win 32-bit (v.2020) EXE | ZIP | Mac OS X (v.2020) | Linux (v.2020) |
| Win 64-bit (v.2020) EXE | ZIP | ||
Legacy versions: | ||
| Windows (v.2014) EXE | ZIP Windows (v.2013) EXE | ZIP | Mac OS X (v.2013 alpha) | Linux (v.2013 alpha) |
Best Data Visualization Software
OpenSignals Mobile
This is a slimmed down version of OpenSignals specifically designed to run on a mobile phone or tablet, while preserving the ease-of-use and performance for real-time sensor data visualization and recording.
Download for your OS
Features
Reliable and intuitive | Extensive list of signal | Open and collaborative | Interoperable |
| Real-time and offline data visualisation for desktop and mobile | FREE event generation (actions) add-on for basic real-time biofeedback | FREE software base, ready to use upon installation (no license keys needed) | Available for Windows, Mac OS, Linux and Android |
| Support for devices with Bluetooth, BLE* and WiFi connectivity | User-friendly data analysis and feature extraction add-ons for raw data post-processing | Cloud-based storage option with interfaces for Google Drive, Dropbox and RepoVizz | Exporting to ASCII, HDF5 and EDF formats compatible with Matlab, Python, and mainstream platforms alike |
| Simultaneous data acquisition from up to 18 channels (3 devices) | Result exporting in CSV format (compatible with MS Excel) or as a PDF report | Flexible architecture that allows you to build your own signal processing workflows | Option to import data stored in ACK (AcqKnowledge) format |
| Possibility to schedule data acquisition sessions | NEW pay-per-report option, with low-cost in-app access to results from individual files | Option to record based on synchronization signals received from third-party systems | Add comments and tags to the recorded files as metadata available for future reference |
| Automatic reconnection to a device (e.g. to recover from battery replacement operations) | FREE real-time and offline statistics about the collected data | ||
| * Currently only on Windows and Android |
Add-ons
Beyond the base data acquistion, visualization, and playback functionalities, OpenSignals also has a suite of signal processing and reporting add-ons, which enable data analysis and feature extraction directly from the acquired data without having to do any coding.
Plugin | Description | Sample Report | |
|---|---|---|---|
| Electrodermal Activity (EDA) Events | Electrodermal responses are characterized as phasic changes in the skin conductance, and associated with the sympathetic nervous system activation. This plugin has been designed to compute overall statistics, basic spectral analysis, and extract typical event-related phasic features from Electrodermal Activity (EDA) sensor data. | ||
| Electromyography (EMG) Analysis | Muscle activity is usually assessed using temporal and spectral features. With this plugin, you will be able to extract useful statistical information from Electromyography (EMG) sensor data. Its automatic onset detection algorithm enables the analysis of each individual muscle activation event, in addition to the overall analysis of the recording session. Timings analysis is also done for each activation relative to a reference muscle. | ||
| Heart Rate Variability (HRV) | Heart Rate Variability (HRV) provides important quantitative markers related with the sympathetic or vagal activity. This plugin enables the seamless extaction and analysis of temporal, spectral, and non linear parameters from Electrocardiography (ECG) or Blood Volume Pulse (BVP) sensor data. All the algorithms were implemented according to the 'Standards of Measurement, Physiological Interpretation, and Clinical Use' devised by the joint European Society of Cardiology and North American Society of Pacing Electrophysiology task force. | ||
| Respiration Analysis (PZT & RIP) | Respiratory data provide useful information about the breathing dynamics. Designed to work with Respiration (PZT) and Respiration (RIP) sensor data, this plugin is a convenient way to determine respiratory rate and other useful temporal and statistical parameters associated with the respiratory cycles. | ||
| Video Synchronization | Multimodal data acquisition in human studies usually involves recording data from sources other than the biosignal acquisition hardware devices (e.g. video camera). Given that the biosignal hardware and the camera are independent recording sources, a common problem when replaying the recording session is the synchronization of both. This plugin was created to provide an easy way to replay biosignal data synchronously with video using for example our LED accessory to provide a common event to both devices. | ||
| Force Platform | Force data can be used for several applications. Center of gravity distribution, jump analysis, weight assessment and force production capacity are just some of applications. This plugin allows you to observe, in real-time, the center of gravity and the force produced in each moment. | ||
| Ergoplux Muscular Load | Muscle Load plugin evaluates the muscular load that the muscles are subjected during a normal work day. It measures the static, median and high intensity levels. | ||
Staff Picks
Target Platform | Description | Kudos to | |
|---|---|---|---|
| Android | BITadroid OpenSignals-like application for Android OS | David G. Marquez | |
| Android | BITalino DataLogger Data logger for Android OS | Borja Gamecho Ibañez EGOKITUZ | |
| Python toolbox for biosignal processing | Pattern and Image Analysis Group (PIA) IT - Instituto de Telecomunicações | ||
| Matlab GUI for ECG, EDA & EMG processing | Athena Nouhi & Sarah Ostadabbas Northeastern University | ||
| Python module for onset detection within Electromyography (EMG) sensor data | Margarida Reis Instituto Superior Técnico (IST) | ||
| Python module for real-time feature extraction from Electrocardiography (ECG) and Electrodermal Activity (EDA) | Valtteri Wikström | ||
| ServerBIT (r)evolution: Service-like barebone of the OpenSignals architecture for rapid prototyping using a Python backend and data streaming in JSON format over WebSockets | João Gomes & Hugo Silva Escola Superior de Tecnologia (EST), Instituto Politécnico de Setúbal (IPS) | ||