SPIRIT Receives Best Student Paper Award at the 2024 Symposium on VLSI Circuits

(Left to Right) Prof. Rikky Muller with co-lead authors Aviral Pandey and Adelson Chua, pictured at the 2024 IEEE Symposium on VLSI Circuits.  

We are honored to announce that “SPIRIT: A Seizure Prediction SoC with a 17.2nJ/cls Unsupervised Online-Learning Classifier and Zoom Analog Frontends” by Adelson Chua*, Aviral Pandey*, Ryan Kaveh, Sina Faraji Alamouti, Justin Doong, Rikky Muller; University of California, Berkeley, has been selected to receive the Best Student Paper Award for the 2024 IEEE Symposium on VLSI Technology and Circuits! Each year, the VLSI Symposium has presented a Best Student Paper Award to encourage the research of student projects that will lead the next generation. Only one paper is selected each year. Congratulations to the whole SPIRIT team, and particularly to Aviral gave an outstanding talk at the conference!

SPIRIT is an SoC integrating an unsupervised online-learning seizure prediction classifier with eight 14.4μW, 0.057mm2, 90.5dB dynamic range, Zoom Analog Frontends. SPIRIT achieves, on average, 97.5%/96.2% sensitivity/specificity, predicting seizures an average of 8.4 minutes before they occur. Its classifier consumes 17.2μW and occupies 0.14mm2, the lowest reported for a prediction classifier by >134x in power and >5x in area.