Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 1.17M | Year: 2012
DESCRIPTION (provided by applicant): The objective is to build and clinically assess PDRemote, a system for automated telehealth diagnostics for remote Parkinson's disease (PD) monitoring. Currently in the United States, there are approximately 1.5 millionpatients living wit PD and 50,000 new cases reported each year. However, there is limited access to movement disorder specialist centers for a significant portion of this population as well as limited opportunity for remote continuous monitoring of motorsymptoms to capture complex fluctuation patterns and optimize treatment protocols. PD is characterized by tremors of the fingers, hands, head, and neck, bradykinesia (slowed movements), and rigidity of musculature. Treatments include pharmaceutical interventions such as levodopa and surgical procedures such as deep brain stimulation (DBS). It is important to accurately quantify motor function and disability in PD to assess intervention efficacy. Currently, subjective clinical rating scales, most commonly the Unified Parkinson's Disease Rating Scale (UPDRS), are used to show clinical improvement in PD. While the UPDRS has shown clinical utility, it requires presence of a clinician for scoring and only obtains a snapshot of symptoms during a clinical office visit. Furthermore, access to movement disorder specialists for effective motor symptom monitoring and management is critical for a geographically disparate subset of the PD population or those unable to travel. The location of movement disorder centers canlimit access to well-trained clinicians and effective symptom management for many PD patients. Telehealth technologies that can improve access for these patients can have a significant impact on the equity, accessibility, and management of the condition for remote patients or those unable to travel. PDRemote will provide remote, automated, motor symptom severity scoring to accurately quantify intervention effectiveness and limit the required number of office visits for treatment adjustments, thereby improving outcomes and decreasing costs for disparate patient populations. PD patients will be sent home with patient kit including an ergonomically designed touch-screen tablet PC, intuitive software interface for diaries, and a wireless motion sensor unit. Data collected from home sessions will be wirelessly transmitted to an online database that generates a motor symptom severity report for clinicians to review via a web-based interface and video conference with a patient to make appropriate medication changes. Feasibility was demonstrated in Phase I by patients successfully using the patient kit in the home to perform motor assessments and clinicians successfully using the web-based application to prescribe tests and view reports. Phase II will further improveergonomics, data transfer, reporting capabilities, and result in a clinically deployable technology. The system will be employed in a multi-center clinical trial to determine if using the system can reduce fluctuations, decrease office visits, and improve patient outcomes. PUBLIC HEALTH RELEVANCE: Parkinson's disease is primarily characterized by motor symptoms of tremor, bradykinesia (slowed movements), and rigidity which can be very debilitating, leading to decreased mobility, independence, and quality of life. Clinicians lack quantitative tools for more continuous monitoring that capture how motor symptoms fluctuate during the day in response to treatment protocols to help minimize Parkinson's motor symptoms. PDRemote will be a repeatable, automated system clinicians will use to remotely monitor PD motor symptoms on a more continuous basis in a patient's home that should improve outcomes and decrease costs especially for disparate patient populations in areas not in close proximity to movementdisorder specialists.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 1.50M | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, implement, and clinically assess a portable, user-worn, bradykinesia feature extraction system, BradyXplore , for integration with Great Lake Neurotechnologies' (GLN) Kinesia and Kinesia HomeView technology platforms for objective Parkinson's disease (PD) monitoring. There has been tremendous research into PD treatments including pharmaceutical interventions and deep brain stimulation (DBS). While tremor is often the most visible symptom, bradykinesia can be the most impairing. The current standard in evaluating bradykinesia is the Unified Parkinson's Disease Rating Scale, a subjective, qualitative ranking system. Scoring instructions for bradykinesia integrate multiple movement features intoa single score that increases variability and limits exploration into if particular bradykinesia features are influenced by specific treatments. If different bradykinesia features were better quantified, novel therapies may be developed to target specificbradykinesia manifestations. The proposed innovations include 1) compact, user-worn motion sensors that can be used with web-based software on a home computer or tablet, 2) algorithms that use kinematic data to rate speed, amplitude, and rhythm independently, and 3) web-based applications for system delivery, patient interaction, and symptom reporting, all of which will promote clinical acceptance and a self- sustaining business model. Wireless motion sensor units containing accelerometers and gyroscopes will be worn on the finger and thumb and collect synchronized motion data. BradyXplore will independently rate speed, amplitude, and rhythm for the standard repetitive motion tasks. Sensor unit batteries will be recharged by an inductive, USB charge pad to eliminate the need for patients to fidget with small connectors. When sensor units are placed on the pad, kinematic data will be transferred to the patient's computer or tablet via a wireless link and then uploaded to our HIPAA-compliant server. In Phase I,our existing motion sensor unit was successfully upgraded to reduce size and improve sensitivity. Algorithms were developed for independently rating speed, amplitude, and rhythm. The algorithms output scores highly correlated to clinical ratings and demonstrated a differential response of speed, amplitude, and rhythm to medication. Phase II will improve ergonomics, sensitivity, data transfer, and reporting. Hardware will be upgraded to include two synchronized sensor units that recharge via an inductive pad and transfer data via a low-power radio. Software will be modified to be completely web-based so patients need not install any software. BradyXplore algorithms will be further investigated in a clinical study to demonstrate its test-retest reliability compared to clinical ratings and determine if speed, amplitude, and rhythm fluctuate differentially ON DBS. We hypothesize that BradyXplore will 1) provide a standardized platform for bradykinesia assessment that objectively quantifies speed, amplitude, andrhythm, 2) receive high clinical acceptance from both clinicians and patients, and 3) aid in development, evaluation, and optimization of therapies such as DBS and pharmaceutical interventions. PUBLIC HEALTH RELEVANCE: Parkinson's disease affectsapproximately 1.5 million people in the United States causing motor symptoms, of which one of the most debilitating is bradykinesia (slowed movements). Bradykinesia is currently evaluated using a subjective rating scale that gives a single score taking into account speed, amplitude, fatiguing, hesitations, arrests in movement, and how these variables change over time. The proposed BradyXplore bradykinesia feature extraction system will separately quantify specific features of bradykinesia (speed, amplitude,and rhythm) in the home, which should aid in the development of novel therapies to target a patient's specific bradykinesia manifestations.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 2.86M | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, build, and clinically assess ParkinStep, an innovative neurotechnology that integrates wireless motion sensing, automated home-based Parkinson's disease (PD) gait and balance assessment, anddeep brain stimulation (DBS) parameter estimation using a web-based database model to integrate data across clinical centers. Following DBS surgery, programming of stimulation settings is performed in the clinic to optimize treatment effectiveness. Upperextremity motor symptoms such as tremor, bradykinesia (slowed movements), and rigidity are typically evaluated in response to DBS settings. Although gait and balance are critical components to quality of life measures and lower extremity dysfunction can bedisabling, current in-clinic evaluations are limited. The time required for stimulation to fully impact gait and balance may exceed the typical time of a programming session. While the effect of DBS on tremor may be almost immediate, obtaining feedback onstimulation effectiveness, gait and balance may require in excess of three hours when stimulation settings are adjusted. From a programming standpoint, the effect of stimulation settings on gait and balance is less understood than with other motor symptoms, possibly due to the complex motor circuits involved in gait. ParkinStep will address these concerns through home monitoring to fully capture the effect of stimulation and possible fluctuations experienced throughout the day. In addition, the patient data collected during home tests will be continuously compiled into an online HIPAA-compliant database to automatically output suggested stimulation settings. Therefore, clinicians, independent of geographic location or programming experience, will have access to this service for improved DBS programming outcomes of gait and balance. The clinical system resulting from Phase II development will 1) allow high compliance home monitoring of PD gait and balance symptoms in response to DBS, 2) allow clinicians to optimize PD response to DBS using a stimulation parameter estimation model, and 3) address geographic disparities of patient clinical access to evaluate gait and balance impairment. This will be achieved by modifying our existing Kinesia HomeView system forlower extremity wear and high compliance in the home settings. The system will be evaluated in a multi-center clinical study to populate the online database to train the DBS parameter estimation model. Finally, the developed model will be used in a clinical impact study to determine whether the ParkinStep system can achieve improved gait and balance response to DBS over traditional methods. PUBLIC HEALTH RELEVANCE: Fall risk associated with gait and balance impairment in Parkinson's disease (PD) patients can cause significant disability and negatively affect quality of life. Programming of deep brain stimulation (DBS) parameters to treat PD gait and balance symptoms is significantly more challenging than for other symptoms including tremor and bradykinesia. ParkinStep: Automated PD Gait and Balance Assessment for Optimizing DBS is an innovative neurotechnology that integrates wireless motion sensing, automated home-based gait and balance assessment, and DBS parameter estimation using a web-based database model to improve programming outcome and patient quality of life and reduce healthcare costs.
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase II | Award Amount: 1.38M | Year: 2015
DESCRIPTION provided by applicant The objective is to engineer build and clinically validate DBS Expert an expert system for optimizing postoperative programming of deep brain stimulation DBS in patients with movement disorders such as Parkinsonandapos s disease PD The clinical utility of DBS for treatment of PD is well established However great outcome disparity exists among recipients due to varied postoperative management particularly concerning DBS programming optimization Many programmers have only a cursory understanding of electrophysiology and lack expertise and or time required to determine an optimal set of DBS parameters from thousands of possible combinations DBS Expert will improve outcomes and equalize care across the country for patients not in close proximity to DBS specialty centers The primary innovations include automated functional mapping based on objective motion sensor based motor assessments that will intelligently navigate the DBS parameter space to guide the programming session and intelligent algorithms that will find a set of parameters that optimize for efficacy while minimizing side effects and battery usage The clinically deployable DBS Expert system will include wireless wearable motion sensors a tablet software app and secure cloud storage The app will include a simple interface to guide the programming session collect all sensor and stimulation data and adjust DBS settings For typical use the system will start by performing automated monopolar survey to determine the patient specific functional anatomy around the lead site and narrow the search space for determining an optimal set of programming parameters This therapeutic window will be valuable at the initial postoperative programming session and simplify subsequent adjustment sessions In Phase I subjects with PD wore our existing Kinesia motion sensor while prototype software guided an automated monopolar survey Stimulation was incrementally increased at each contact until symptoms stopped improving or side effects appeared Search algorithms were successfully developed to automatically identify optimal DBS stimulation parameters Parameters chosen by the algorithms improved symptoms by nearly or maintained therapeutic benefits while reducing stimulation amplitude to decrease battery usage Phase II will include developing an app to integrate the successful Phase I prototype functional mapping software with DBS IPG programmer communication protocols to streamline use a multi center clinical evaluation to optimize specific functional mapping protocols and parameter space navigation algorithms and integration of the optimal search algorithm and bidirectional communication protocols into a commercially viable product We hypothesize DBS Expert will improve patient outcomes access to care clinician and patient experience battery usage and frequency and duration of follow up programming sessions compared to traditional programming practices PUBLIC HEALTH RELEVANCE The clinical utility of deep brain stimulation DBS for the treatment of movement disorders such as Parkinsonandapos s disease has been well established however there is a great disparity in outcomes among DBS recipients due to varied postoperative management particularly concerning the choosing of an optimal set of programming parameters from the thousands of possible combinations The proposed system will use motion sensor based assessments to develop a functional map and intelligent algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption
Great Lakes Neurotechnologies | Date: 2013-03-05
The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subjects movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subjects symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMU) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subjects with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 242.97K | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, develop, and clinically validate MyoSense , a clinician worn, high-resolution sensory enhancing prosthetic to quantitatively characterize and distinguish different types of muscle hypertonicity. Development will focus on the growing clinical need to differentiate dystonia from spasticity in children affected by cerebral palsy (CP) and other mixed or secondary dystonias. Children with CP often suffer from mixed motor disorders including spasticity, muscle weakness, ataxia, athetosis and dystonia causing severe functional impairment and limiting activities of daily living. Additionally these coexisting motor manifestations can occur in different parts of the body based on brain injury topology.Spasticity and dystonia are both currently measured clinically using subjective, ordinal and non-interval rating scales, thereby limiting applications of statistical techniques in any analysis. Currently, quantitative measures are not widely used althoughrecent studies suggest biomechanical features can distinguish different types of hypertonicity. Distinct pharmacologic and surgical interventions exist for different neurological findings, motor signs, and movements observed for children with CP; therefore, quantitative assessment could better guide clinical judgments for treatments. Consequences for selecting invasive treatments for the incorrect diagnosis can have significant, long term consequences. Additionally, a general, quantitative assessment system for examining muscle tone should have important applications in several other movement disorders including Parkinson's disease, stroke, and general rehabilitation. The MyoSense system will provide a compact, user worn prosthetic instrumented with kineticand force sensors and integrate real-time software feedback to guide a standardized and quantitative motor examination. The specific innovation lies in four areas. First, instead of instrumenting a patient, the sensory enhancing prosthetic is worn by theclinician making the device is highly adaptable to measure hypertonia from a wide range of joint sets in a variety of patient and conditions. Second, the integration of multi-modal sensors in a wireless glove measures real-time joint position and velocitywhile simultaneously measuring forces required to move the body part independent of gravity to help distinguish spasticity from dystonia. Third, real-time software display feedback will guide the clinician motion assessment to standardize and quantify features. Finally, intelligent algorithms will process the data and extract features t classify spasticity and dystonia. Phase I will utilize an existing motion sensing hardware platform with the integration of additional sensor modalities to demonstrate feasibility of capturing and quantifying features of spasticity and dystonia. The hardware will be modified to minimize patient and clinician burden by optimizing sensor type and count and embedding the system into a clinician worn glove. A software interfacewill be developed to collect data during clinical studies and provide real-time feedback for an evaluation. Finally, the prototype system will be evaluated in clinical feasibility study. PUBLIC HEALTH RELEVANCE: We will design, develop, and clinically validate MyoSense , a clinician worn, high-resolution sensory enhancing prosthetic to quantitatively characterize and distinguish different types of muscle hypertonicity, specifically differentiating dystonia from spasticity in children affected bycerebral palsy (CP) and other mixed or secondary dystonias. Spasticity and dystonia are treated differently and are both currently measured clinically using subjective, ordinal and non-interval rating scales and as a result selecting the incorrect treatment can have significant, long lasting implications for children with CP. The MyoSense system will provide a compact, clinician worn glove instrumented with kinetic and force sensors and integrate real-time software feedback to guide a standardized and quantitative motor examination so that clinicians can appropriately prescribe treatments that will help improve patient quality of life.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 289.96K | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, build, and clinically assess ParkinStim , a home-based, noninvasive brain polarization system used during sleep to treat Parkinson's disease (PD). While current therapeutic standards of drugintervention and deep brain stimulation (DBS) show effective treatment of PD symptoms, transcranial direct current stimulation (tDCS) is a less expensive and less invasive potential alternative/adjunct treatment with few side effects that may help treat PD symptoms, decrease medication usage, and reduce sleep disturbances. Recent studies have demonstrated that noninvasive anodal tDCS applied to the scalp over primary motor cortex (M1) can improve PD symptoms. tDCS provides polarization to the cerebral cortex via painless weak currents transmitted through noninvasive scalp electrodes. Unlike other noninvasive stimulation modalities such as transcranial electrical stimulation (TES) and rapid transcranial magnetic stimulation (rTMS) that can be painful and cause side effects including seizures and psychotic symptoms, tDCS is painless, poses few side effects, and is ideal for home use since it can be provided in an inexpensive and compact package. The primary innovations of ParkinStim include 1) easy-to-don wearable tDCS hardware suitable for home use, 2) a technique for providing tDCS during sleep, and 3) a therapeutic tDCS system to treat PD symptoms and related sleep disturbances. The proposed system will provide a wearable device that patients with PD can easily don before going to sleep and use through the night. Since patients often feel worst in the morning after medication from the previous day has worn off, stimulation during the night may help patients wake up feeling better. Additionally, designing thedevice for overnight use will make the system convenient and accessible so patients need not worry about using the device in public or during their daily activities. Development will focus on treating the motor symptoms of PD; however, the proposed systemmay prove beneficial for other PD symptoms or related sleep disturbances. For this Phase I, we aim to demonstrate 1) technical feasibility by safely and effectively using existing stimulation and electrode hardware to provide tDCS to PD patients during sleep and 2) clinical feasibility by demonstrating that tDCS reduces PD symptom severities and decreases symptom fluctuations. Ten PD subjects will participate in a counterbalanced crossover clinical study during which tDCS is applied to M1 while the subjectsleeps in a sleep laboratory and standard polysomnography data is collected. Phase I success criteria include safely and effectively administering tDCS to PD patients during sleep without causing waking and demonstrating an acute therapeutic effect of tDCS. While Phase I is designed to evaluate the acute benefits of tDCS, Phase II will investigate the chronic benefits of multiple nights of tDCS used in the home over several weeks. We hypothesize that the final system resulting from Phase I and II development will provide safe and effective tDCS during sleep, decrease PD symptom severities, minimize motor fluctuations, reduce required medication, and improve sleep quality. PUBLIC HEALTH RELEVANCE: Parkinson's disease affects nearly 1.5 million Americans with annual treatment costs approaching 25 billion. While current therapeutic standards of drug intervention and deep brain stimulation (DBS) show effective treatment of PD symptoms, transcranial direct current stimulation (tDCS) during sleep is a less expensive and less invasive potential alternative/adjunct treatment with few side effects that may help treat PD symptoms, decrease medication usage, and reduce sleep disturbances. Successful development will result in a safe, easy-to-use home-based tDCStherapy system PD patients can use during the night to feel better during the day.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 283.83K | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, build, and clinically assess DBS-Expert, an expert system for optimizing the postoperative programming of deep brain stimulation (DBS) systems in patients with movement disorders such as Parkinson's disease (PD). DBS-Expert will use motion sensor based assessments to develop a functional map and algorithms for navigating the programming parameter space that maximize symptomatic benefits while minimizing side effects and battery consumption. The clinical utility of DBS for the treatment of movement disorders such as PD is well been established. However, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning DBS programming optimization. Most programmers have only a cursory understanding of electrophysiology and lack the expertise or time required to determine an optimal set of DBS parameters (contact, polarity, frequency, pulse width, and amplitude) out of the thousands of possible combinations. DBS-Expert will remove the guesswork from programming and take the responsibility out of the hands of the clinicians by providing an expert system that efficiently determines appropriate DBS settings. DBS-Expert will be designed for useby a general practitioner or nurse rather than by a neurologist or neurophysiologist with years of experience in DBS programming and disease management. For the first postoperative programming session, the DBS-Expert will perform an automated monopolar survey. The patient will wear our existing motion sensor unit and perform motor assessments at various DBS settings. Stimulation will be incrementally increased from zero at each contact until symptoms stop improving as measured by a motion sensor unit or side effects appear. The monopolar survey will help determine the functional anatomy around the lead site and narrow the search space for determining an optimal set of programming parameters. This therapeutic window will be valuable at the initial postoperative programming session as well as all future adjustment sessions. In Phase I, we aim to demonstrate technical feasibility by developing software for automated functional mapping of the DBS programming parameter space and clinical feasibility by developingalgorithms that efficiently navigate the programming parameter space and output settings that reduce symptoms, side effects, and battery usage as well or better than would an expert clinician programmer. Ten subjects with PD and a DBS implant will participate in a clinical study in which the DBS-Expert prototype guides the subjects through assessments as part of a constant-current monopolar review. A functional map will be developed and algorithms will determine an optimal set of DBS settings. Subject symptom severities, side effects, and battery usage will be compared to that of an experience DBS programmer. The final DBS-Expert system resulting from Phase I and II development will greatly expand the accessibility of DBS for patients not located near specialized centers by removing the programming burden from a few expert clinicians thereby equalizing care across the country. PUBLIC HEALTH RELEVANCE: The clinical utility of deep brain stimulation (DBS) for the treatment of movement disorders such asParkinson's disease has been well established; however, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning the choosing of an optimal set of programming parameters from the thousandsof possible combinations. The proposed system will use motion sensor based assessments to develop a functional map and algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 249.82K | Year: 2012
DESCRIPTION (provided by applicant): The objective is to design, implement, evaluate and commercialize an innovative web-based education system targeted to enhance high school curriculum by stimulating early understanding of neuroscience knowledge, imagination of neuroscience applications, and interest in neuroscience careers. The scaleable MyNeuroSci system will integrate two signal modality options including innovate instrumentation and/or simulations and web-based modules for neuroacquisition, neuroanalysis, and neurogaming. This student- centered learning tool will reinvent the way high schools can integrate neuroscience with limited overhead to promote a positive impact in neuroscience knowledge and careers. Once the global leader in science and technology, the U.S. currently lags behind other countries. Economic growth can be stimulated through education investments and the field of neuroscience greatly contributes through new medical technologies and scientific careers. However, technological advancements and new career opportunities must be bootstrapped by promoting a strong understanding and interest in neuroscience during pre-college education. For America to remain competitive, our next generation must develop critical- reasoning and problem-solving skills that can be provided by foundations in neuroscience. Simple to implement, cost efficient learning tools that can easily integrate into high school curriculum should provide a solid foundation for students to recognize neuroscience opportunities,acquire a neuroscience knowledgebase, and expand critical reasoning and problem solving skills. Furthermore, it is critical learning tools are scalable and appropriate across genders, race, and wide ranging socioeconomic conditions so all students have opportunity to engage neuroscience and contribute to careers, technology development, and economic growth. The project will integrate CleveMed's expertise in lab instrumentation, neurosignal acquisition and analysis, and web-based software with the educationexpertise of Project Lead the Way, a world leader in high school curriculum development. While previous work provides a strong foundation, this program requires significant new development and integration. New curriculum and materials must be developed topromote interest and understanding across wide ranging high school and student demographics. CleveMed's extensive neurosignal database will be organized for access from web-based simulations and a wireless acquisition system optimized for cost effective,simple implementation. Scalable learning modules will provide options for student signal recording, neurosignal simulation, integrating neurosignals in gaming applications, processing and analysis, and interpretation and reporting. A web-based software infrastructure will be implemented. Providing web- based access will minimize costs associated with software maintenance, ensure students are always using the latest tools, and allow access anywhere an Internet connection is available. Finally, educational impact studies will ensure the system enhances neuroscience knowledge acquisition and interest in neuroscience careers. PUBLIC HEALTH RELEVANCE: The objective of this Fast-Track proposal is to design, implement, evaluate and commercialize an innovative web-based education system targeted to enhance high school curriculum by stimulating early understanding of neuroscience knowledge, imagination of neuroscience applications, and interest in neuroscience careers. The scaleable MyNeuroSci system will integrate two signal modality options including innovate instrumentation and/or simulations and web-based modules for neuroacquisition, neuroanalysis, and neurogaming. This student- centered learning tool will reinvent the way high schools can integrate neuroscience with limited overhead to promote a positive impact in neuroscience knowledge and careers.
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 1.69M | Year: 2011
DESCRIPTION (provided by applicant): The objective is to design, implement, and clinically assess ETSense , an adaptive, compact, portable essential tremor (ET) monitor for optimizing therapeutic interventions. ET is characterized primarily by postural and kinetic (action) tremors of the limbs, which are rated by various subjective tremor rating scales. These scales all provide a discrete, subjective symptom rating at a discrete point in time, require a clinician to visually assess the patient, and cannotcapture complex fluctuations that occur throughout the day in response to interventions. Objectively capturing ET symptoms continuously during daily activities and using adaptive algorithms to both classify tremor types and severity will help clinicians better titrate therapy to minimize symptom fluctuations and expand care to rural and underserved populations. The Phase I ETSense effort successfully used kinematic data recorded from a sensor unit placed on the finger of subjects with ET to discriminate tremor from voluntary motion associated with daily activities and objectively quantified tremor severity with scores highly correlated with clinicians' qualitative ratings, providing a standardized platform for continuous ET assessment. Tremor quantificationalgorithms were extrapolated to non-standardized tasks, suggesting that it is feasible to rate tremor continuously throughout the day during activities of daily living. The three primary innovations of the proposed system include: 1) a compact, portable, user-worn device for continuous monitoring during ADLs, 2) intelligent, adaptive algorithms to continuously classify tremor type and rate severity, and 3) web-based access to symptom response reports. The clinically deployable system will be contained in alightweight, finger-worn housing for continuous wear while patients perform everyday tasks at home or in public. A push button diary will allow the patient to indicate when medication is taken. All data will be stored in memory for subsequent analysis andreport generation detailing symptom fluctuations in response to therapeutic interventions. Adaptive algorithms developed in Phase I will be further optimized to account for voluntary motion that can create tremor false positives or mask over kinematic tremor signals. The system will shift between scoring algorithms (i.e. rest, kinetic) based on any voluntary motion detected. After data collection is complete, clinicians will use a web-interface to view patient reports. These reports will detail tremor type,severity, and fluctuations, as well as when medication was taken to aid clinicians in optimizing existing therapeutic interventions or in the research and development of novel treatment protocols. We hypothesize that the commercial ETSense system will 1)continuously quantify tremor severity throughout the day during activities of daily living, 2) improve patient outcomes with better and/or faster medication optimization, 3) decrease healthcare costs by reducing office visits, and 4) enable the testing andvalidation of novel therapeutic interventions, facilitated by high-resolution continuous home monitoring. PUBLIC HEALTH RELEVANCE: Essential tremor, characterized primarily by tremor during movement, affects approximately 4% of the population overage 40 in the United States, though exact prevalence may be much higher since up to 90% of ET patients do not seek treatment. The proposed ETSense adaptive, portable essential tremor monitor will classify tremor type and rate tremor severity continuously throughout the day while a patient performs typical activities, which should help clinicians to better prescribe treatment and aid in the development of novel therapeutic interventions.