These are questions that occupy the minds of researchers in the Multi-Modal Motion Synthesis Laboratory the M3 Lab, part of the Sensory Motor Systems Lab at the ETH in Zurich, Switzerland. Answers are found in a controlled research environment that comprises a variety of display, recording, and tracking technologies. When combined they create a multi-modal, user-cooperative system for sport applications. The M3 Rowing Simulator was the first application that was implemented in which the sensitive dynamics of rowing combined with haptic, visual, and acoustic feedback provides a challenging background for a sports simulation scenario. Qualisys is proud to be part of this exciting and almost futuristic journey, to bring sports and general movement training to a new level.
Visual, Acoustic, and Haptic Feedback
The M³ Lab differs from other so-called cave environments that usually comprise only visual and auditory modalities, by adding a third modality addressing the user’s haptic senses. This is brought to reality thanks to the Reactive Rope Robot (r³) that connects multiple ropes to an end-effector. In the rowing-simulation, the rope robot is attached to the oar blade where it generates forces to simulate water resistance.
The M³ Lab system further consists of a visual display surrounding the viewer with 3D visual information such as a river scenario. A sound system exposes the user to virtual sound sources such as a cheering audience or water splashing. A ten-camera Qualisys 3+ motion tracking system monitors the orientation and position of various segments or single markers of the rower.
Low latency real-time system
In today’s consumer-driven market we are spoiled with choices and the decision-making process is often a difficult and lengthy one. In order not to be side-tracked during this process, consumers should have a very clear picture in mind of what goals they want to bring to reality with their new purchase – long and short-term.
Peter Wolf, Senior Researcher at the Sensory-Motor Systems Lab, knew one thing for certain when he started looking for new technology for the M3 Lab – it had to meet and preferably exceed his criteria for low latency in a real-time system. Qualisys recognized, early on, the importance of the real-time performance / low latency combination and, therefore, foresaw a number of features to natively optimize the real-time performance. Once the Qualisys system was installed at ETH, the lab performed a series of latency tests to quantify the performance.
Latency Determination Test
ETH measured movements simultaneously using an incremental wire potentiometer (0.25 mm resolution, sampling at 1000 Hz) and a ten-camera Oqus-300 system running at 200 Hz. The wire potentiometer was directly linked to an xPC target; latency was assumed to be negligible. Marker positions were also received at the xPC target via UDP from a computer running Qualisys Track Manager, 2.1. Both data streams were sent from the xPC target to a host computer where latency was quantified.
The monitored movement was based on the sliding of a seat in a rowing boat, repetitively performed forward and backward over a distance of 0.6 m at about 1.6 Hz. Movement was performed along one axis of the global coordinate system defined for motion capture, thus, the related coordinates of the tracked object representing the seat’s movement (with markers placed on it) was compared to the potentiometer also measuring the seat’s movement. The experiments were repeated with additional, static objects that were also tracked.
At the host computer at the end of the chain, data from the Qualisys system running at 200 Hz was received every 5 ms (4 to 6 ms, 5th to 95th percentile). Latency of the motion capture system was determined also at the host computer. Depending on the number of supplementary static objects, latency varied from six to seven milliseconds. This equates to just a fraction over a one frame delay in real-time data capture to process and display of data.
“We appreciate that Qualisys deals with our research-specific demands by optimizing data processing and implementing communication protocols that minimize latency during data streaming.”
Senior Researcher, Sensory-Motor Systems Lab