Software

Explore a range of both official and community-contributed software tools and data visualization software. 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.

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.2017) is available here


Download for your OS

Latest version available: September 20 2017 (win/mac)

Win 32-bit (v.2017)
Win 64-bit (v.2017)
Windows (v.2014)
Windows (v.2013)
Mac OS X (v.2017)
Mac OS X (v.2013 alpha)
Linux (v.2017)
Linux (v.2013 alpha)

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.

android opensingal

Download for your OS

Android (v.2017 beta)

Staff Picks

Target Platform

Description

Kudos to

Android
bitalino play
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)
 

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. PDF
included free of charge
in the following kits:
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. PDF
included free of charge
in the following kits:
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. PDF
included free of charge
in the following kits:
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. PDF
included free of charge
in the following kits:
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.
included free of charge
in the following kits:
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.
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