About Us
Σ 3SP Mission:
Strengthen
Significant Signals
Σ 3SP – also Sig3 – is devoted to strengthening the clinical MEG and EEG imaging communities’ SNRs significantly.
Sig3’s goal is to increase the signal to noise ratio of the user’s raw data, as well as data analysis and new indications’ training and support.
Our founders have worked together for over fifteen years with over 50 years of combined experience in the MEG and signal processing industries.
Bringing you better data for better patient analysis analysis through noise reduction is our team’s goal – all without traditional filtering!
Long story short
Dr. Taulu’s doctoral and first company work dealt with suppressing various interference suppression, head movement compensation, and data standardization purposes.
Dr. Taulu explained how his patented widely now used SSS and tSSS software came about:
Early on my colleagues and I were interested in developing methods that would make infant MEG recordings and data analysis possible. This challenge required novel mathematical theories to be developed for compensation of movement-related signal distortions that are so prevalent in the MEG recordings of awake infants.
“My colleagues and I developed the general physics-based signal space separation (SSS) method for the purpose, which, due to its general nature, not only solved the movement compensation problem but also provided MEG users with a very effective and objective interference suppression method.”
After Dr. Taulu started working at the I-Labs at the University of Washington (Seattle), Mr. Otto inquired about his newer research endeavors. Because heard Dr. Taulu had found shortcomings with tSSS, namely dealing with a small number of channels (sensors) or possible inaccuracies, he set about for possible software remedies. Listening to Dr. Taulu’s goals, they agreed that the medical imaging community would be well served by providing the results of Dr. Taulu’s efforts, and the result was Sig3’s being born.
Most importantly Sig3 – and Dr. Taulu’s team at I-Labs – has taken a holistic approach in looking at signal quality improvement by noise suppression. That is, the signal chain starts with intrinsic sensor problems and on to the second link with external environmental interference.
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