Bio-Well and Blood Sugar: What a 102-Person Study Found

Could patterns recorded in a fingertip scan be associated with fasting blood sugar? A study discussed by Bio-Well explored that question in 102 participants. The research raises questions about electrophotonic imaging (EPI), also called gas discharge visualisation (GDV), but it does not establish that a scan can diagnose diabetes or replace a blood test.

What the researchers investigated

Bio-Well’s article describes a 2016 paper by Bhat, Deo, Mavathur, and Srinivasan from S-VYASA University in Bangalore, India. The researchers compared EPI measurements with fasting blood sugar to look for statistical relationships.

According to the source, 200 people were screened and 102 were included in the analysis. The others were excluded because of incomplete data or image-quality problems. Participants came from yoga camps and the university’s health centre, so this was not a representative sample of the wider population.

How the study was organised

Each participant received a fasting blood sugar test and a ten-finger EPI scan. The researchers analysed imaging parameters such as area, intensity, entropy, and software-defined organ-sector readings, using regression analysis to examine their associations with blood sugar.

The source reports three groups: 29 participants in the normal blood-sugar group, 13 in the prediabetic group, and 60 in the diabetic group. These were the study’s groupings, not diagnoses made by the fingertip scan. The groups were analysed separately.

What Bio-Well’s summary reports

The source describes correlations between selected imaging parameters and fasting blood sugar, with different patterns across the three groups. It characterises the normal group’s associations as more general, the prediabetic group’s as involving pancreas and right-kidney sectors, and the diabetic group’s as involving multiple sectors.

These sector names belong to the imaging system’s interpretive framework. A correlation involving a software-defined pancreas or kidney sector is not a direct measurement of that organ’s function, damage, or disease.

Different groups do not prove disease progression

Bio-Well’s article interprets the group differences as a possible pattern of progression. However, the study was cross-sectional: it compared people at one point in time. It did not follow the same people as they moved from normal blood sugar to prediabetes or diabetes.

The findings therefore cannot establish that an EPI scan detects early changes before conventional tests, predicts who will develop diabetes, or tracks how an individual’s condition progresses. Those questions require longitudinal research and independent validation.

A related study explored classification

The source also discusses a companion 2016 study by Kumar and colleagues involving 200 participants from a diabetic centre in Bangalore. It describes the use of a neural-network classifier to attempt to distinguish diabetic and non-diabetic participants from EPI data.

Classification is a different question from correlation. Neither approach, as summarised in the supplied article, establishes that a commercial Bio-Well scan is a validated diabetes screening or monitoring tool. Related studies from the same research setting also do not substitute for replication by independent teams.

The limitations that matter

The main study had 102 participants, and only 13 were in the prediabetic group. Findings based on such a small subgroup need particular caution. Recruitment from one setting and the exclusion of many screened participants also limit how confidently the results can be generalised.

Most importantly, correlation is not diagnostic accuracy. A statistical relationship does not tell us whether a scan can reliably identify diabetes in a new patient, avoid false alarms, or rule out abnormal blood sugar. The source itself distinguishes the findings from a diagnosis and calls for larger studies.

What this means for readers

The study is best understood as exploratory research into associations between EPI parameters and a conventional metabolic marker. It is not evidence that Bio-Well measures glucose directly, replaces laboratory testing, or provides a basis for changing diabetes treatment.

Do not use a Bio-Well result to diagnose or rule out diabetes, adjust medication, or delay recommended testing. Decisions about blood sugar and diabetes management should be made with a qualified healthcare professional using established clinical assessment and tests.

The takeaway

The reported associations are a starting point for further investigation, not a replacement for a blood sugar result. The useful distinction is between a pattern that researchers observe in a study and a test that has been validated for decisions about an individual’s health.

Sources and further reading

Bio-Well: How Bio-Well detected blood sugar patterns: the diabetes study (18 April 2026).

Bhat RK, Deo G, Mavathur R, and Srinivasan TM (2016). Correlation of Electrophotonic Imaging Parameters With Fasting Blood Sugar in Normal, Prediabetic, and Diabetic Study Participants.

Kumar and colleagues (2016). Electrophotonic Imaging Based Analysis of Diabetes. Companion study cited by the source.

This article is an original summary of Bio-Well’s account, not an independent review of the underlying study data. The source is published by the company marketing Bio-Well. This content is for general information and is not medical advice.