biosignalsplux ergoResearcher

All the hardware and software essentials for full powered ergonomic teams managing injury prevention and missed working days. This kit objectively measures muscular load according to released standards (ISO 5349-1:2001).

Included Hardware
  • 1x wireless 8-channel hub with 16GB internal memory
  • 1x Electromyography (EMG) sensors
  • 1x Bluetooth dongle
  • 1x medical-grade charger
  • 24x pre-gelled & disposable electrodes
  • 1x portable & rugged storage case
  • 4h personalized technical support
Included Software (Digital Content)

Work-related musculoskeletal disorders are a world problem, concerning health, social and economic sectors. In fact, the high prevalence of such disorders in the spine and upper limbs have been documented by several studies associated with to a higher number of work absences and dissatisfaction, which leads to significant social and economic costs.

With this in mind, this kit was designed to objectively track and measure work-related stress on workers conducting physical work processes by providing reliable data for ergonomists to detect, prevent, and/or improve high-risk work activates. This kit aims to help decrease and prevent the amount of work-related musculoskeletal disorders. The ergopResearcher uses the OpenSignals (r)evolution software and the Muscle Load Analysis software add-on to track the muscular stress of workers by acquiring Electromyography signals (up to 8 sensors simultaneously) and by analyzing the muscle contraction intensities over time.

The Electromyography (EMG) Analysis add-on allows extracting statistical information from the acquired signals to evaluate the stress workers are exposed to in further detail. Additionally, the Video Synchronization add-on allows the users to record videos of the workers during the signal acquisition sessions to visualize all signals synchronously with the recorded video for post-acquisition analysis purposes (e.g. movement analysis).

Hub
Analog ports 8 generic inputs
Auxiliary ports 1 ground & 1 digital I/O
Resolution Up to 16-bit (per channel)
Sampling rate Up to 3kHz (per channel)
Communication Bluetooth Class II
Range Up to ~10m (extendable)
Internal memory 16GB
Battery life ~10h streaming; ~24h logging
Size 85x54x10mm
Weight 45g (without sensors)
Color White
EMG Sensor
Gain: 1000
Bandwidth: 25-500Hz
CMRR: 100dB
Range: ±1.5mV (with VCC=3V)
Input Impedance: >100GOhm
Cable Length: 100cm±0.5cm (customizable)
OpenSignals Signal Processing Add-Ons

The biosignalsplux ergoResearcher includes the following add-ons for our OpenSignals (r)evolution software.

Electromyography (EMG) Analysis

This add-on is designed to extract useful statistical temporal and spectral information from electromyography data acquired with the Electromyography (EMG) sensor. Its automatic onset detection algorithm is designed to detect muscle activations in the EMG signal, allowing the user to select and derive activation-specific parameters for further analysis of the EMG signal. The onset detection algorithm can be fine-tuned for application-specific muscle activation detection by defining the frequency ranges of interest using the available low pass, high pass, and band pass filters.

Find Out More


Muscle Load Analysis

The Muscle Load Analysis add-on is designed for online (during the acquisition) and offline (post-processing) evaluation of muscular load in ergonomics, biomechanics, and sports research applications, and is the ideal software extension for the biosignalsplux Electromyography (EMG) sensor. It measures the muscular load that muscles are subjected during a period or task (e.g. during a normal work day or work process) according to Jonsson’s method of Amplitude Probability Distribution Analysis (APDA) of acquired EMG signals.

Find Out More


Video Synchronization

The Video Synchronization add-on for the OpenSignals (r)evolution software is the ideal software extension for the synchronization of video and biosignal acquisitions. Multimodal data acquisitions in a variety of research fields include video recording setups as complementary data to the acquired biosignals.

Find Out More

You might also like these