Frequently Asked Question (FAQ). Click on topics below for more details
Basically the device works on the principle of trans reflectance spectroscopy technique where there is a glucose specific led placed inside the device which will emit light and this light will help in detecting the glucose values during measuring of the finger.
Device will use transreflectance spectroscopy, where visible light will provide transmission data and infrared light will provide reflectance data. Along with this occlusion of the tip will help in increased penetration of NIR, and device design will help in prevention of sray light interaction. Chemometric predictive model will convert the detected transmitted and refected light data into glucose values.
As of now the device is 70% accurate. We are going to collect the data of 20000 patients and making the device + or – 2% compared to analytical readings.
NIR is not at all harmful for humans. Example BSX Athletics and Moxy Monitor wearable monitors using NIR spectroscopy to measure muscle oxygenation.
Patient’s data is automatically stored in the application. Around 30 readings can be stored in the device.
The app which is interlinked to the device has different parameters to feature which include diabetic diet suggestions for patient, questionnaires to know whether the person is diabetic or not, storage of the data.
Yes, there are other devices which are in the process of developing. CNOGA, Diamontech, Helo Extenze, Glucowise, Orsense. Glucoise and Diamontech are still underdevelopment. Helo Extenze has still not scured any approvals.
Yes, we applied for CDSCO it is under process we will get the approval by the end of 2019. After CDSCO we will also apply for FDA.
Yes, doctors can access the data of their patients on the app for better healthcare of their patients.
Yes, doctor can connect with their patients and vice-versa during any emergencies or fr any information.
Yes, the app contains diabetic diet suggestions and etc.
Yes, the data provided in the app authenticated by best diabetologists.
All the patient data will be securely uploaded to an encrypted cloud service for further imprvment of the algorithm for achieving better results.
Along with glucose value device also detects, Diabetic neuropathy, Insulin site, Diabetic foot ulcer, Diabetic Ketoacidosis.
Yes, the device has a voice readout facility for the blind people, so that they can know their blood glucose values and other parameters6
The device has no limitations for type 1 and type 2 diabetic patients, it works similarly for both the diseased conditions giving the accurate results.
All the type 1 diabetic patients need to measure their glucose readings 5 times per day.
All the type 2 diabetic patients need to measure their glucose readings 5 times per day.
The device consists of monofilament which helps in detecting the diabetic neuropathy condition in diabetic patients earlier to its onset.
The device consists of a breath sensor which helps in detecting the acetone levels from the breathe this will help in analysing the diabetic ketoacidosis condition in the particular patient.
The device consist of a temperature sensor which helps in detecting the foot temperature in particular patients. In every diabetic foot ulcer patient there is an increased dorsal foot temperature upto 4 to 5 degrees than normal patient foot temperature, this situation can help in measuring the foot temperature with temperature sensor which helps in detecting the foot ulcer condition.
The device consists of a vernier callipers attached to it which helps in measuring the skin fold thickness at various insulin sites. In diabetic patients due to regular insulin shots they are more prone to lipodystrophy conditions, to prevent this the skin fold thickness measurement helps in understanding the more fat tissue present areas by detecting this the insulin shot site rotation can be done which will help the patient in reducing the lipodystrophy conditions.
The device can be used on diabetic foot ulcer patients also, by measuring the temperature of the foot if it is high or low based the patient can be advised with wound healing treatment or guidance.
The device can be used on diabetic neuropathy patients also.
Device works on the basis of Trans-refetance spectroscopy.
Trans-reflectance spectroscopy is the simultaneous and conitinuous use of visible light for collection of transmissio data and infra red light for reflectance data collection.
Red light and infra red light are used for glucose detection in the device.
675 nm (red light) is used.
940nm and 1100nm (infra red light) is used.
Few glucose specific wavelengths are selected by performing preliminary analysis on the glucose solutions using ocean optics spectromete
Extensive phantom tissue model study is performed, where multilayered tissue phantoms containing epidermis, dermis, hypodermis, blood vessels, blood and bone like components with similar optical properties as their named tissues. Various levels of glucose concentrations are prepared and injected into the phantoms to accquire in-vitro data for detection of highly glucose specific wavelength.
Possible outcomes include: Highly glucose specific wavelength will be determined, biological interferences which cause errors can be reduced to a minimum level.
Yes, all the parameters are interlinked with each other in the device.
Sample size is 0-800 mg/dl with an intervals of 1mg/dl. Each sample data is collected as triplicate.
Collected data will be analysed for highly glucose specific wavelengths using chemometric analysis using unscrambler X software (CAMO analytics).
Biological interferences of skin, melanin pigmentation, tissue absorption and scattering, blood moleucle interference, bone, finger nail interferences. Water and fat absorption errors can also be identified and removed using in-vitro testing and chemometric analysis.
Device design will help in maintaining uniform pressure on any type of finger irrespective of its thickness, negating the errors which can be developed due to variable pressure on fingers.
Occlusion of blood at the fingertip will increase the glucose concentration and enhace the finger optics helping in deeper penetration of NIR light.
LED placement will help in reducing the skin roughness errors for obtaining maximum reflectance data.
Stray light interference can be negated by device structure, as it will prevent the stray light from interacting with the nir light source and detector.
Other device structures installed in the device are IR temperature sensors (for foot ulcer detection), acetone sensor (for ketoacidosis detection), retractile monofilament (for neuropathy detection) and skinfold detection device (for insulin shot site detetion).
Physiological errors caused by heart rate, blood pressure, skin temperature etc can be incorporated into the algorithm for prevention of errors.
Diabetic ketoacidosis is the most common complication for all diabetic patients. In diabetic ketoacidosis patients or patients who may prone to diabetic ketoacidosis will have fruity smelling breathe which is nothing but the release of ketone bodies from persons breathe. In the device we will be having an acetone sensor which will detect the acetone levels from breathe and will analyse the condition of the diabetic ketoacidosis in a particular patient.
The data required to detect diabetic ketoacidosis is various diabetic people breathe data are collected and the collected data is used to develop a suitable algorithm and integrated in the device which will give the readings of the acetone levels.
There is only one sensor required to collect the data for diabetic ketoacidosis that is acetone sensor.
Sample size required to develop algorithm will be not more than 1000 patient data.
The device consists of monofilament which helps in detecting the diabetic neuropathy condition in diabetic patients earlier to its onset. When the person feet is subjected to this monofilament and when the monofilament bends to c shape, if the person experiences no sensation to the feet then the person is suffering with diabetic neuropathy.
The data required to detect diabetic neuropathy is various diabetic people feet data are collected using the monofilament test and these data are integrated in the device.
Sample size required to develop algorithm will be not more than 1000 patient data.
Diabetic foot ulcer can be detected using dorsal foot temperature fluctuations, with the help of IR temperature sensors installed in the device. The temperature sensor will sense the temperauture fluctuations and record in the device, which will then analyse and provide reports on the presence or absence of diabetic foot ulcer.
Data required to develop foot ulcer detection is various dorsal foot temperature of different diabetic individuals by using this data the algorithm will be built and integrated into the device.
IR Temperature sensor is required to collect the data for foot ulcer complication.
The sample size required to develop the algorithm should be of minimum 1000 patients foot temperature data.
Inuslin absorption at a particular site is dependent upon the subcunateous tisse thickness layer. This thickness can be identified by relating with skin fold thickness at particular given sites. Device will have a installed skinfold calipers which will help in measuring of skin fold thickness, using such skinfold values device will analyse and inform whether that site is optimum for insulin injection.
The data required to detect insulin shot site selection will be of different skin fold thickness measurements of the diabetic patients and based on that data the algorithm is built or it can be directly measured by checking the skin fold thickness of a person who is measuring and where ever the skin fold thickness is less that can be taken as a insulin shot.
The sample size required to develop insulin shot site selection will be about 500 patient data.