Adaptive & Individualized AAC

The heterogeneity of the more thanof Americans who suffer from severe physical impairmentsSPIspreclude the use of common augmentative or alternative communicationAACsolutions such as manual signsgestures or dexterous interaction with a touchscreen for communicationWhile efforts to develop alternative access methods through eye or head tracking have provided some communication advancements for these individualsall current technologies suffer from the same fundamental limitationexisting AAC devices require patients to conform to generic communication access methods and interfaces rather than the device conforming to the userConsequentlyAAC users are forced to settle for interventions that require excessive training and cognitive workload only to deliver extremely slow information transfer ratesITRsand recurrent communication errors that ultimately deprive them of the fundamental human right of communicationTo meet this health needwe propose the first smart AAC system designed using individually adaptive access methods and AAC interfaces to accommodate the unique manifestations of motor impairments specific to each userPreliminary research by our team of speech researchers at Madonna Rehabilitation HospitalCommunication Center Laband Boston UniversitySTEPP Labutilizing wearable sensors developed by our groupAltecInchave already demonstrated that metrics based on surface electromyographicsEMGand accelerometer measures of muscle activity and movement for head mediated control can be combined with optimizable AAC interfaces to improve ITRs when compared with traditional unoptimized AAC devicesLeveraging this pilot workour team is now proposing a Phase I project to demonstrate the proof of concept that a single sEMG IMU hybrid sensor worn on the forehead can provide improvements in ITR and communication accuracy when integrated with an AAC interface that is optimized through machine learning algorithmsThe prototype system will be tested and compared to a conventionalnon adaptableinterface in subjects with SPI at a collaborative clinical siteAssistance by our speech and expert AAC collaborators will ensure that all phases of technology development are patient centric and usable in the context of clinical careIn Phase II we will build upon this proof of concept to design a smart AAC system with automated optimization software that achieves dynamic learning which adapts to intra individual changes in function through disease progression or training as well as inter individual differences in motor impairments for a diverse set of users with spinal cord injurytraumatic brain injurycerebral palsyALSand other SPIsThe innovation is the first and only AAC technology that combines advancements in wearable sensor access with interfaces that are autonomously optimized to the userthereby reducing the resources and training needed to achieve effective person centric communication in SPIthrough improved HMI performance and reduced workload This project addresses the fundamental mission of NIDCDNational Institute for Deafness and Communication Disordersto provide a direct means of assisting communication for people with severe physical impairments caused by strokehigh level spinal cord injuryneural degenerationor neuromuscular diseaseLeveraging wearable access technologywhich has barely been explored for AAC userswe will develop a first of its kind adaptive tablet interface tailored to individual users through advanced movement classification algorithmsThrough these effortswe aim to provide an improved Human Machine InterfaceHMIthat is able to accommodate varying degrees of interand intra subject residual motor function and context dependent impairments to provide individuals with SPI the opportunity for improved societal integration and quality of life