# Development of a Medical Device Utilizing an EEG-Based Algorithm for the Objective Quantification of Pain

> **NIH NIH R44** · PAINQX, INC. · 2020 · $526,563

## Abstract

Project Summary / Abstract
Chronic pain affects over 100 million Americans representing a major public health imperative. Objective
biomarkers of pathology exist for several diseases, and their development is one of the great advances of modern
allopathic medicine; however, objective assessment of pain has lagged far behind.
Currently, there are no objectively verifiable and clinically useful means to identify or quantify the presence or
severity of pain. The current standard of care relies on patient self-report, such as the visual analog scale (VAS),
which presents a serious barrier to the effective assessment and treatment of pain. Self-reported pain is
influenced by nociceptive, affective, and cognitive processes, and though many treatments effect reported pain,
they likely do so through a varied set of neurophysiological mechanisms, with different consequences for health
and long-term well-being. Some patients have difficulty assigning themselves a pain rating, especially those with
pain that falls towards the middle of the rating scale. In addition, communications issues, drug-seeking behavior,
the desire of some patients to appear stoic, and other issues can create problems with establishing an accurate
pain rating. As a result, despite a long history of research, current assessment and treatment of pain is not
optimal, with enormous costs to patients and society.
PainQx is currently developing the PQX-MED system, a system that will objectively evaluate an individual’s pain
level using quantitative EEG (QEEG). Advanced signal processing, machine learning, classification
methodologies and a large reference database will be used to develop algorithms that quantify features of an
individual’s EEG that are associated with the perception of pain.
Before the PainQx platform is ready for its FDA Validation Study, PainQx needs to demonstrate the ability to
assess pain in a representative set of patients with chronic pain. To ensure commercial viability, PainQx also
needs to be able to generate its pain biomarker using a limited montage of EEG electrodes which can be rapidly
applied prior to data acquisition and processing.
PainQx proposes to achieve these objectives through the proposed SBIR project. In Phase I, PainQx will conduct
a clinical study of 50 chronic pain patients utilizing 19 lead EEG acquisition, add those cases to an existing
database of 19 lead pain cases, and demonstrate that 19 Lead EEG data can be used to assess the intensity of
pain a patient is experiencing. In Phase II, PainQx will demonstrate that the relationship between the VAS and
a QEEG based biomarker demonstrated using 19 leads can be demonstrated using a subset of EEG recording
locations to significantly improve clinical utility. Further, predictive accuracy using the reduced montage will meet
targets for performance established using 19 lead data.

## Key facts

- **NIH application ID:** 9968212
- **Project number:** 5R44DA046964-03
- **Recipient organization:** PAINQX, INC.
- **Principal Investigator:** William Koppes
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $526,563
- **Award type:** 5
- **Project period:** 2018-07-15 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9968212

## Citation

> US National Institutes of Health, RePORTER application 9968212, Development of a Medical Device Utilizing an EEG-Based Algorithm for the Objective Quantification of Pain (5R44DA046964-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9968212. Licensed CC0.

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