Professor Joe Jabre, a native of Lebanon, is a US Neurologist with special training in Clinical Neurophysiology. His academic career spans a 45-year research interest in Electromyography, Single Fiber and Macro EMG, Motor Control and Cortico-Motoneuronal connections, EMG Signal Decomposition techniques, Near Infra-Red Spectroscopy (NIRS) study of peripheral nerve oxygenation, and the development of the e-norms method to derive normal values from clinically indicated EMG studies. He is currently participating in the Norway DIGMINE (formerly e-norms Norway) project at Oslo University for big data collection and analysis of nerve conduction studies and its AI applications in the pattern detection and analysis of nerve conduction data. To date, the DIGMINE project has collected over 220,000 nerve conduction studies from seven major hospitals in Norway including the studies of over 500 patients between 0-2 years of age and 7,000 patients over 80 years of age. Dr. Jabre is the former Chief of the Harvard and Boston University Neurology Service at the Boston VA Medical Center, and until recently, a Clinical Professor of Neurology at the University of California in Los Angeles-UCLA.

The extrapolated normal values (e-norms) project started in 1996 while we were trying to collect nerve conduction studies (NCS) normal values for our EMG laboratory at the Boston VA Medical Center. To do so we were “encouraging” secretaries, medical students, residents, and the occasional spouse or significant other to lend us their limbs for a 20-30 minutes nerve conduction study to collect normal values. We quickly realized the shortcomings of our effort since none of those volunteers would ever become a patient in a US Veterans Administration hospital, and any data collected from them would dramatically skew our studies’ interpretation making even our healthiest older veterans patients look abnormal. This led us to explore a review of NCS data we interpreted as “normal” or negative in our Lab to determine whether or not they could be used as a substitute for our collection of normal values, and proceeded to upload hundreds of these data into an Excel spreadsheet for analysis. A fortuitous plotting of our data sorted by the variable we were analyzing, rather than by age, resulted in an inverted S curve we had not previously encountered. Interestingly, we noticed that the datapoints where the curve changed directions (its min and max inflection points), closely resembled the normal min and max normal values we were using in our Lab for that same variable. We then posited, and subsequently confirmed, that descriptive statistics of the data that lie in the flat part of the curve between its two inflection points, must then closely resemble the normal descriptive statistics we were using in our Lab for that same variable. In my presentation, I will go over a description of the e-norms method; its use for many other data than just nerve conduction studies, including serum blood samples and BMI among many others; the Excel Macros we developed for its everyday use; its web-based application that to date has gathered close to 1.5 million data points from over 20 countries; and the great difficulty we encountered in getting it accepted for publication in 2015, nearly 20 years after we first developed it. Drs. Matthew Pitt and Jacquie Deeb were my co-authors on this first publication. To date there are 20 publications referencing the e-norms method for deriving normal values from a Laboratory population, as well as three novel methods that appeared in the literature since then replicating the e-norms principle for calculating normal values from Laboratory data.