FLTR- Frequency+ampLitude Recorder of Tremors

Affordable, accessible,non-invasive and portable device for measuring characteristics of tremors to aid in diagnosis of movement disorders.

For millions of people in the world, their body is their worst enemy. Simple everyday tasks like holding a cup of tea, filling the crossword puzzle, cutting their nails, are next to impossible because of tremors in their bodies. They live in a body that cannot support their mind. Tremors affect nearly 5% of the population above the age of 40 years, but so many of these tremors go undiagnosed and untreated. Tremors are considered a side effect of ageing, rather than a pathology. The severity of a problem lies not just in its mortality, but also in its morbidity.

Involuntary,oscillatory movements which may dwell in varied parts of the body are referred to as tremors.They are very important clinically, their characteristics forming the pillars of diagnosis of a myriad of diseases.Thus, their characterization holds immense value.Tremors are classified on the basis of  frequency, amplitude,  distribution and provoking circumstances. Present criteria rely heavily on easily observable findings like site of tremor, provoking circumstances and and associated symptoms to analyse the tremor, making examination of tremors much too subjective. Our prototype is an attempt to reduce said subjectivity by quantifying one such characteristic that is the frequency of tremors,till now. We are attempting to expand the domain of application of our prototype, such that it can measure other characteristics of a tremor, as well as aid in other aspects of a CNS exam.

The prototype is very compact and powered by a battery and hence, is mobile. It is inexpensive and non invasive with no apparent risk to the health of the patient. It can be used to detect tremors in many different parts of the body, not just the limbs.

The prototype has tremendous potential for use in Resource Poor Health Care setups where due to lack of efficient clinical training, medical practitioners often miss the diagnosis of this class of disorders, or diagnose it when it is too far along.Frequency detection will help remove the veil of subjectivity from what is right now hugely ,a clinical diagnosis.Not only aiding in diagnosis and prognosis of tremors but also providing new public health care data from all around the world.

The standard technology used for detection and characterization of tremors
presently, is expensive, bulky, invasive and requires expertise for
interpretation. Thus, interfering with diagnosis and treatment of movement
disorders, especially in resource poor settings.Our prototype, poses to be a
cheap, portable, non invasive counterpart which can simply run on a battery and is elementary to interpret making it ingenious. Compared to similar non
invasive techniques for tremor characterization, ours requires no add on
technology like computers for displaying and interpreting results, making it
cheaper and more useful in said resource poor settings.There is work going to
make it so compact that it can become hand held.

Our prototype uses a sensor, which can count the oscillatory movements of the part of the body which is affected. This is then sent as an input, which is interpreted by our code to calculate the frequency of tremors and displayed on a screen. We are working on being able to use machine learning to interpret this frequency and provide a diagnosis, but it is a work in progress and not yet a part of the existing prototype.

Over the next 12 months, we aim to test the existing prototype clinically. Also we wish to incorporate machine learning into it and incorporate characterization of tremors along other parameters as well, such as its amplitude. We then plan on applying for a patent.

After completing the patenting process,we aim to apply to became a registered medical device in India.If we get money from SOLVE, we wish to use it to manufacture a few test models to send to Not for profit organisations to allow us to use their existing channels to distribute the device, giving us the data to apply for Grants, as well as expand our network of Not for profit organisations to get the money we need to manufacture the device.We also in parallel wish to incorporate machine learning into the device so it can even further provide provisional diagnoses.

After possibly patenting and registering the device, we plan to manufacture test models to send to Not for profit organisations to ask them for using their existing channels to distribute our device.Then we plan to apply for Grants, as well as expand our network of Not for profit organisations to get the money we need to manufacture the device. Since we are proposing the use of existing distribution channels, we expect minimal expenses on that front. Our device is very easy to use and we will educate people by holding training sessions both for patients and their health care providers. 

None, since our product is in prototype stage of development.

Over the next 12 months, we aim to test the existing prototype clinically and test the device more comprehensively to apply for a patent as well as approval as a registered medical device over the next 3-5 years, then distribute it with the help of Not for profit organisations.With this we will be changing the lives of many, not only by making a device for tremor measurement available in settings where previously its diagnosis was rare but also by generating important public health data among population groups where it was previously not available.

Our team consists of 3 undergraduate students and our mentor who specializes in movement disorders making us a unique amalgamation of individuals not only possessing skills necessary to engineer the device but also delve into the disorder's intricacies and procure clinical data efficiently and easily.Since we frequently interact with patients, we can bridge the divide in communication between developers and  beneficiaries of a device. We have access to manifold resource poor health care settings,giving us the information about the challenges such health care providers face.Intertwining of passion and information is what we hope helps us stand out.

We plan to test the device more comprehensively, apply for a patent as well as approval as a registered medical device in India over the next 3-5 years.If we get money from the SOLVE challenge, we wish to use it to manufacture a few test models which we will send to Not for profit organisations throughout the country to use their existing channels to distribute the device. This will give us the data we need to apply for Grants, as well as expand our network of Not for profit organisations to get the money we need to manufacture the device. Since we are proposing use of existing channels of distribution, we expect minimal expenses on that front. We have made a device, such that its very easy to use but we will again be using the channels of our not for profit partners to educate the patients on what are movement disorders as well as the need to monitor them, by holding training sessions both for patients and their health care providers. Thus,the cost comes down mainly on manufacturing the device, which is intentionally inexpensive, and has scope for coming down further.

We are applying to SOLVE for mentor ship and support. With special emphasis on procuring help in introducing our device in countries other than India,and for validation by the U.N.This could help us not only publicize our device,but also help us generate even more varied and resourceful public health data, to reveal information about movement disorders to aid in research and their possible treatment. We are always open to collaborations researchers, entrepreneurs and policy makers which SOLVE will help us with.

As a 2 month old team,SOLVE will help catalyze the process of getting our product to its beneficiaries. The main barrier is getting Not for profit organisations to understand our idea and agree to help and fund us. SOLVE will give us the funding and validation we need to make our device a reality.It will also allow us to conduct clinical testing more comprehensively, possibly even getting data from other countries.Our team consists of all members firmly rooted in the field of medicine. To proceed further as efficiently as we want to,we need technological mentor ship.