A novel approach in confronting hand tremor. Team Members

Transcription

1 ARISTOTLE UNIVERSITY OF THESSALONIKI Dept. of Electrical & Computer Engineering Telecommunications Division Thessaloniki, Greece A novel approach in confronting hand tremor Team Members Angeliki Papathanasiou (January 9, 1995) is an undergraduate student at the Electrical & Computer Engineering Dept. of Aristotle University of Thessaloniki. Her fields of interest include Biomedical Engineering, Signal Processing Analysis and Pattern Recognition. She enjoys playing chess and in her leisure time she enjoys dancing. She acts in TremorFreeMe as a Signal Processing Engineer (paangeliki@auth.gr). Basian Lesi (September 16,1994) is an undergraduate student at the Electrical & Computer Engineering Dept. of Aristotle University of Thessaloniki, Greece. His fields of interest include Electronics and System control. He acts in TremorFreeMe as a Hardware Engineer (lesimpas@auth.gr). Thomas Bikias (September 22, 1995) is an undergraduate student at the Electrical & Computer Engineering Dept. of Aristotle University of Thessaloniki, Greece. He is a Microsoft Student Partner. Electromagnetics and Remote Sensing are the fields he is interested in. He enjoys watching and playing Football in his free time. He acts in TremorFreeMe as a Software Engineer (bikiast@auth.gr).

2 The Problem Tremor is a progressive disorder defined as an unintentional muscle movement in the human body. The causes of its presence vary, depending on the different types of tremor, and in many cases they are considered undefined. It is the most common of all involuntary movements and although it can affect different parts of the body, most tremors occur in the hands. The most well-known forms of tremor are Essential Tremor (ET), Parkinsonian Tremor (PT), Cerebellar tremor (CT) and Drug induced tremor (DIT). Tremor is neither life-threatening nor contagious. However, tremor is a life-altering condition, and affects every aspect of a person s life. Tremor s progression is marked by the presence of several recognized problems in their everyday physical activities. These include coordination problems, writing difficulties, and patient s incapability of completing vital daily self-managing tasks, such as getting dressed, eating, or even drinking a glass of water. It is evident that the escalation of the latter conditions progressively leads to embarrassment, isolation and depression due to decreased self-esteem and socialization. The age of onset is typically over 40 years, while 15% of people with the condition develop "young-onset" tremor before reaching age 40. It is estimated that 10 million people suffer from ET only in U.S.A, while 6.3 million people worldwide suffer from Parkinson s Disease, with no differentiation for race or culture. Tremor has a strong footprint at the economical field, as brain disorders produce only in Europe, a steadily increasing annual cost of more than 200 billion. Although investigation has been conducted for more than a century, many questions remain open in terms of pathophysiology and treatment options of tremor. Despite several advances in the understanding of drugs actions and in the surgical techniques, the tremor cannot be fully or sufficiently controlled in about 40-50% of patients. Pharmaceutics, which provide only partial relief, often cause undesirable side effects, while surgery, thalamotomy or Deep Brain Stimulation (DBS), can cause notable neurological and psychiatric side effects such as hemorrhages and sometimes increased suicidal tendency. From the latter emerges the need for an innovative cost-effective method for tremor reduction, thus improving patient s quality of life. TremorFreeMe Our Vision Motivated by the aforementioned, TremorFreeMe proposes an intelligent ICT-based approach to assist people who suffer from tremor. TremorFreeMe introduces a novel medical wearable device which aims to fight tremor and improve patients quality of life. It provides patients with a holistic platform, which manages to monitor tremor behavioral characteristics and changes, and, thusoffers a personalized aid by controlling the tremor intensity. The ultimate goal is to enrich our data collection, train our suppression device and reach high level of intelligence, which will lead to a fully personalized functional approach for each user. This way, the patients can deal with tremor in their daily routine and counter problems relating to feebleness for selfmanaging task and daily physical activities, emotional shift towards depression. TremorFreeMe Architecture Community 2

3 The structure of TremorFreeMe involves a pool of participants more than 40+ yrs old that form the TremorFreeMe community (Fig. 1). The number of members of this community is expected to continuously grow across the use of TremorFreeMe, taking into account the prevalence of essential tremor and PD in the older adults and the awareness initiatives of TremorFreeMe via the social media and the already established collaborations with relevant communities, e.g., the International Federation on Ageing (IFA, the International Essential Tremor Foundation (IETF, the American Parkinson Disease Association (APDA, the European Parkinson s Disease Association (EPDA, To further support the expansion of the TremorFreeMe community, TremorFreeMe will target relatives of already patients as about 50% of people with ET have another affected member of the family and relatives of already diagnosed PD patients have approximately 5-10% increased risk. Tremor Suppression Module Our tremor suppression module consists of a smartphone/smartwatch that connects with the Microsoft Azured, along with a custom-made device, which is designed to detect the involuntary activation of agonist muscles and activate the antagonist muscles and vice versa. Thus, by detecting the involuntary movement and producing the opposite one, we manage to reduce tremor and stabilize the hand (Fig. 2). Tremor analysis: Tremor characteristics, amplitude and frequency, are primary quantitative clinical factors for monitoring of tremors. We implemented an algorithm for tracking the frequency and amplitude of tremor from inertial sensor measurements (3 axis gyroscope & accelerometer). Fig. 1.The general architecture of TremorFreeMe. The algorithm has as initial value the patient s tremor fundamental frequency, which is normally measured during a clinical diagnostic procedure. The output adapts to the current dominant tremor frequency based on the measurements of the gyroscope. The adaptation is done after the application of a noise-reduction filter, in order to avoid fast changes in the estimated frequency. Fig.2. The Tremor Suppression Module of TremorFreeMe. 3

4 Device Functionality: Our team is building a fully functional autonomous battery-powered wearable device which is still in the prototype stage (Fig.9). Its main function is to detect the involuntary tremulous movement, using data from a 3-axis gyroscope & accelerometer and deliver electrical stimulations through small electrode pads, in order to reduce tremor. For that purpose, we developed an algorithm that is able to make real time decisions and efficiently stimulate the opposite muscles of the ones activated due to tremor, achieving significantly high tremor suppression (Fig.3). Fig. 3. Angular velocity [deg/sec] vs. Time [sec]; showing the tremor reduction during the activation period of the device. Safety: The aim of TremorFreeMe is to provide an above-identified electrical stimulation device that avoids the drawbacks of known stimulation devices and allows for simple and quick application and safe stimulation even over several days.the voltage supply is provided from a 3.7V lipo battery. The muscle stimulation is achieved under 10-25mA biphasic current pulses of 30-50μs duration. It is completely safe, even in a short circuit situation, (that can be caused by water throwing) since the 22μF capacitor cannot discharge any dangerous current and the two 30mA fuses prevent any unwanted current flow above 30mA by shutting down the whole system. The battery has been tested at its maximum discharge rate by connecting both poles. Biphasic current pulses are used to avoid any skin irritation that can happen from one way current flow. 4

5 Fig.4. Device PCB Design First-level Personalization: The optimal parameters, in order to achieve the highest tremor reduction, vary from person to person. For this reason, we are developing a Machine Learning (ML) model in Azure ML studio. At the first stage, the algorithm takes decisions of whether or not to deliver a stimulation based on the default parameters (auto mode). After a small training period (in which we evaluate each stimulation given) our ML model is able to predict if a stimulation should be given or not. This way, at the second stage, the default parameters change to the optimal ones for the specific patient, achieving a high level of personalization. Users Classification (Second-level Personalization): The increase of patients who use the device and the grow of the TremorFreeMe Community can lead to an extra improvement of the first-stage (auto mode) of the device, and thus,an upgrade of the personalized care provided to the user. TremorFreeMe aims at the creation of a big data collection of tremor processed features, i.e., amplitude, tremor frequency, which are stored in Azure Cloud. ML techniques are used to classify patients based on these features combined with complementary user s characteristics (sex, age), in order to predict which tremor suppression model will be optimal for them. This way one patient s data from the first-level personalization, can allow another one to start with an already adapted model, instead of the default one. Benefits from Tremor Suppression: TremorFreeMe provides patients with a fully functional wearable device that suppress tremor. It aims at helping patients complete everyday vital activities, such as eating and drinking, and giving them the opportunity to experience every situation a healthy person can, like typing on a computer, painting, reading a novel etc. Also, TremorFreeMe contributes to the reduction in the drugdependency and allow the patients schedule their daily routine free-of medicine effect periods. This way, they can stand on their feet and they will feel empowered, confident and, most of all, emotionally secured from embarrassment and depression. Technologies Used 5

6 Hardware: Android Wear, Mobile Phone, TremorFreeMe custom-made device. Software: Azure Services Machine Learning Studio, Mobile App, Push Notifications, Azure Active Directories, WordPress page Development Tools: Visual Studio 2015 Community, Arduino IDE Other Technologies: Cross Platform Developing (Xamarin), C#, Matlab, LUIS (Language Understanding Intelligence Service User s Interface: Android application for Mobile or Android Wear, that communicates and controls TremorFreeMe Device, via Bluetooth, by switching it on-off and adjusting the intensity of the pulses. The app is based on background tasks, always taking into consideration low battery consumption and Internet connectivity. More specifically, while online, application sends the parameters (velocity, time in period) to azure ML to achieve the First-level Personalization. Moreover, if a similar and effective patients-model found, user will be notified and will be prompted to update his current model for better suppression results (Users Classification (Second-level Personalization)). In order to use the application, every user must register and submit some personal and medical information. TremorFreeMe application, automatically and locally, saves data and user s preferences. This way, users can use the application offline and their data will be auto-synced when device can access the Internet. Fig. 5. Screenshots from the TremorFreeMe Mobile App Privacy Awareness 6

7 The bloom of big data is accompanied by the quest for privacy aware learning. Privacy is important because training data are of highly sensitive kind. Distributed processing, i.e., on the very acquisition side is important both for reducing communication resources and for supporting privacy. More specifically, all data are sent encrypted to our servers, which are Microsoft Azure Servers that follow all the privacy standards. In particular, Windows Azure cloud platform allows customers to meet Health Insurance Portability and Accountability Act (HIPAA) regulations on business associate agreements. We try to automate the process of data analysis by making some of it directly on the user s device. This means that only some numbers (features) travel to our servers and not sensitive, raw data. The identity of each participant will be kept confidentially at the site of data collection and will not be shared amongst consortium partners or any other group. Each participant will be assigned a coded identification number once they provide informed consent. Pilot Case Study At the moment (April 2017), TremorFreeMe team is conducting a Pilot Case Study in a close collaboration with the Parkinson's Disease Greek Association. Twenty patients are engaged in testing TremorFreeMe device (Fig. 9), providing us with the necessary data and feedback to adjust our proposals to their exact needs. Neurologists (i.e., Dr. Bostantzopoulou, Full Neurologist Professor, AUTH) and the SPBTU of AUTH ( provide us with the appropriate medical guidance and Research and Development (R&D) requirements, respectively. Fig.9.Photos from the realization of TremorFreeMe Pilot Case Study. How could you take this further? TremorFreeMe is a revolutionary system aiming at providing integrated solutions to the basic problem related with tremor, i.e., patients feebleness to complete daily self-managing activities. Using cutting-edge technology, TremorFreeMe provides a novel approach to the tremor problem by organizing a supportive community, providing information and engagement to its members towards an innovative cost-effective medical device, emphasizing on personalized health, promoting active and healthy aging from a world citizenship perspective. Updates and improvements of the current solution include: Cross-case testing and evaluation of the feedback from the target group, regarding the expandability and functionality of 7

8 TremorFreeMe, gained through ongoing contact with tremor patients, older adults and doctors further customization of service to different tremor types and behaviors. TremorFreeMe team has made a considerable work towards the development and realization of TremorFreeMe project. So far, the whole project has been designed and an important part of it has been realized. Given the complexity and the importance of the addressed problem, implementation issues, evaluation procedures, testing, and optimization are still under consideration. Our prototype is in a fully operational mode. In the near future, we expect to test our prototype to a large group of users and increase its efficiency by improving the design and adjusting it to the real needs of the users. 8