Developing a multidimensional pain detection device for infants


To develop a device that detects, measures, and continuously reports pain levels in infants in neonatal intensive care units

Anticipated Impact: 

Better pain management for preterm babies


Infants in the neonatal intensive care unit (NICU) often require painful life-saving and life-sustaining procedures. The pain experience is neurologically toxic to the developing brain and is associated with long-term behavioral, cognitive, and learning difficulties. Thus, precise pain detection in preterm babies is key to effective and safe treatment in the NICU and potentially better outcomes later in life. Currently, pain in the NICU is measured by clinical observations and the use of “pen and paper” pain scales. These are subjective, unreliable, and valid for only the specific moment in time that the infant is observed. Dr. Schiavenato, a former NICU nurse, is developing a product to detect, measure, and report pain level continuously and objectively at the bedside. The device will integrate three different indicators of pain and report a “pain score” via a glass orb that changes color according to severity. Methods to measure two of the three pain signals have been developed. The LSDF grant supports collaborations among researchers at WSU’s Spokane and Pullman campuses to (1) develop methods to capture the third pain signal; (2) refine algorithms to calculate composite pain scores; and (3) construct a prototype. The team anticipates commercializing this technology by licensing the underlying intellectual property to a medical device manufacturer.

A supplement was awarded to support salary, which enabled activation of two research awards for a human trial of the prototype device.

Collaborating organizations: Murdock Charitable Trust

Pain Detection, Localization

Grant Update

Principal Investigator:
Martin Schiavenato
Grantee Organization:
Washington State University
Grant Title:
Developing a multidimensional pain detection device for infants
Grant Cohort and Year:
2015 Proof of Concept (03)
Grant Period:
08/16/2015 - 08/15/2018 (Active)
Grant Amount:
Over the last semester, we have met our milestones successfully and have successfully characterized our first lab prototype for facial grimacing. During this period, we have developed a test platform for the silicon fabricated in Feb. 2016 and evaluated its operation against simulated results for the proposed system. Concurrently, we have worked with a team of 5 undergraduate researchers to develop a programmable processor that captures the three signals for pain and merges them using a linear convolutional network to predict pain. The researchers have been able to identify a suitable linear network algorithm using open-source software called LibLinear. Additionally, our team has submitted one conference papers on the fully characterized silicon and is proceeding to submit another journal paper later this semester.

Impact in Washington

Location of LSDF Grantee
Locations of Collaborations/Areas of Impact

Legislative Districts:
3, 4, 6, 9

Health Impacts

Pain Detection, Localization