Newborns are routinely and frequently exposed to pain during Neonatal ICU (NICU) care. Pain assessments in neonates are difficult, labor intensive, subjective and unreliable ? often resulting in excessive or inadequate analgesia. Our overall objective is to measure infant pain objectively, reliably, and in real-time. We will extract pain-related information from multiple non-invasive sensors, develop a sensor fusion framework to integrate multi-modal sensor data into a single pain score, and assess the validity of this approach by comparing with validated clinical pain scores.
Specific aims : 1) To differentiate acute pain from baseline or non-painful events, we will study 60 newborns using: facial electromyography (EMG) to record facial expressions specific for infant pain, electrocardiography (ECG) to measure heart rate changes and heart rate variability, skin conductance to measure catecholamine-dependent palmar sweating, electroencephalography (EEG) using 32 ?active? electrodes to assess pain-related brain activity, and pulse oximetry (SpO2) to record pain-induced changes in oxygenation and peripheral perfusion. We will study acute painful procedures associated with mild, moderate, or severe pain in 30 late preterm (34-36 weeks) and 30 term newborns (37-42 weeks). Bedside nurses will use validated pain scoring methods to concurrently assess these infants for pain. A pain expert will independently assess 50% of subjects, to establish inter-rater reliability and to authenticate the bedside nurses? pain scores. From each sensor, we will extract pain-related data that correlate strongly with the clinically relevant pain scores. 2) To develop sensor fusion frameworks integrating data from multiple sensors. Proprietary machine learning algorithms will fuse pain-related data from all 5 sensors, ?calibrate? itself for each newborn by using data from prior pain events, and compensate for missing or unreliable data. Sensor fusion frameworks including combinations of these sensors will help to identify infant pain with far greater specificity and sensitivity than the subjective pain scales used clinically. Procedures will be included to assess the scaling properties of this objective approach and to refine the principal algorithms. Data analyses will assess inter-rater reliability and internal consistency, verify content, concurrent and construct validity, and include multivariable modeling for optimal selection and weighting of the sensor variables that will compute the final objective pain score. This approach will eventually lead to a bedside ICU monitor (compatible with the ECG, SpO2, EEG, EMG, and skin conductivity sensors), which displays the current pain intensity and trends within the time periods of clinical interest. An objective, automated pain detection device developed for newborns (and adapted for other nonverbal patients) will reduce the subjectivity and variability of pain assessments, improve the safety and efficacy of various analgesics used for treating neonatal pain, avoid the acute side effects and long-term effects of both unrelieved pain or excessive analgesia in newborns, prevent iatrogenic tolerance and neonatal abstinence syndrome, reduce the workload of bedside NICU nurses and improve clinical outcomes. !
Newborns receiving intensive care in the Neonatal ICU (NICU) are repeatedly exposed to acute painful procedures during routine medical care, but it is difficult to determine if they are experiencing pain or not, or their response to pain-relieving therapies. In this pilot study, we will use a novel machine learning framework to develop an automated bedside monitor that is designed to measure pain intensity in newborn infants ? objectively, reliably, and in real-time ? capable of displaying the current pain score as well as trends within time periods of interest to bedside clinicians or parents. Reliably measuring pain in newborns will enhance the safety and efficacy of pain-relieving drugs (like morphine) for treating pain in newborns, thus avoiding the immediate side effects as well as the long-term detrimental effects from unrelieved pain, versus excessive or highly variable drug therapy in the newborn period.
