
Cerebral Palsy Risk Identification SystemAward last edited on: 12/6/2019
Sponsored Program
SBIRAwarding Agency
NIH : NINDSTotal Award Amount
$561,578Award Phase
2Solicitation Topic Code
-----Principal Investigator
James P O'HalloranCompany Information
Phase I
Contract Number: 1R43NS098840-01A1Start Date: 9/1/2018 Completed: 8/31/2020
Phase I year
2018Phase I Amount
$300,502Public Health Relevance Statement:
PROJECT NARRATIVE Cerebral palsy is the most common physical disability in childhood, with a prevalence of 2.1 cases per 1000 in high-income countries. The overall project goal is to develop a computerized hardware-software system capable of identifying preterm infants at high risk of developing cerebral palsy (CP), based on the systematic identification of specific patterns of movement-derived features. The Cerebral Palsy Risk Identification System (CPRIS) will enable clinical staff with only minimal training to cost effectively implement General Movement Assessment (GMA) for Cramped Synchronous General Movements (CSGMs), with interpretive reporting performed automatically. The CPRIS constitutes a key enabling technology for advancement in the identification, characterization and treatment assessment of CP.
Project Terms:
Accelerometer; Acute; Adoption; Advisory Committees; Algorithms; Architecture; Area; Automation; base; Biological Markers; Birth; Brain; Budgets; Cephalic; Cerebral Palsy; Child; Childhood; Classification; Clinical; Clinical assessments; clinical practice; Collaborations; Communication; comparative; computer based statistical methods; computerized; computerized data processing; Consensus; cost; Country; critical period; Data; Data Compromising; data modeling; Data Set; Databases; Development; Developmental Disabilities; Diagnosis; Diagnostic; digital; Disease; Drops; Electronic Health Record; Enrollment; Environment; Equipment; Evaluation; experience; field study; follow-up; Frequencies; Generations; Gestational Age; Goals; Health care facility; Healthcare Systems; heuristics; high risk; improved; Incidence; Income; indexing; Infant; Legal patent; limb movement; Machine Learning; Magnetic Resonance Imaging; Manuals; Measurement; Measures; Methods; miniaturize; Modality; Modeling; Monitor; Motor; Movement; Multicenter Trials; Muscle Cramp; National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; Neonatology; new technology; Optics; Outcome; Patients; Pattern; Pediatrics; Performance; perinatal brain; Phase; Physically Handicapped; postnatal period; Premature Birth; Premature Infant; Prevalence; primary outcome; Production; Progress Reports; prospective; prototype; Provider; Reporting; Research; Research Personnel; Resolution; Risk; Sample Size; Sampling; Sensitivity and Specificity; sharing data; Signal Transduction; software systems; Specialist; Strategic Planning; Stroke; success; System; Technology; Time; tool; Training; Transportation; Ultrasonography; United States; Validation; Video Recording; Weight; Wireless Technology
Phase II
Contract Number: 5R43NS098840-02Start Date: 00/00/00 Completed: 00/00/00
Phase II year
2019Phase II Amount
$261,076Public Health Relevance Statement:
PROJECT NARRATIVE Cerebral palsy is the most common physical disability in childhood, with a prevalence of 2.1 cases per 1000 in high-income countries. The overall project goal is to develop a computerized hardware-software system capable of identifying preterm infants at high risk of developing cerebral palsy (CP), based on the systematic identification of specific patterns of movement-derived features. The Cerebral Palsy Risk Identification System (CPRIS) will enable clinical staff with only minimal training to cost effectively implement General Movement Assessment (GMA) for Cramped Synchronous General Movements (CSGMs), with interpretive reporting performed automatically. The CPRIS constitutes a key enabling technology for advancement in the identification, characterization and treatment assessment of CP.
Project Terms:
3-Dimensional; Accelerometer; Acute; Adoption; Advisory Committees; Algorithms; Architecture; Area; Automation; base; Bayesian Network; Biological Markers; Birth; Brain; Budgets; Cephalic; Cerebral Palsy; Child; Childhood; Classification; Clinical; Clinical assessments; clinical practice; Collaborations; comparative; computerized; computerized data processing; Consensus; cost; Country; critical period; Data; Data Compromising; data modeling; Data Set; data sharing; Databases; Development; Developmental Disabilities; Diagnosis; Diagnostic; digital; Disease; Drops; Electronic Health Record; Enrollment; Environment; Equipment; Evaluation; experience; field study; follow-up; Frequencies; Generations; Gestational Age; Goals; Health care facility; Healthcare Systems; heuristics; high risk; improved; Incidence; Income; indexing; Infant; Legal patent; limb movement; Machine Learning; Magnetic Resonance Imaging; Manuals; Measurement; Measures; Methods; miniaturize; Modality; Modeling; Monitor; Motor; Movement; Multicenter Trials; Muscle Cramp; National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; Neonatology; new technology; off-patent; Optics; Outcome; Patients; Pattern; Pediatrics; Performance; perinatal brain; Phase; Physically Handicapped; postnatal period; Premature Birth; Premature Infant; Prevalence; primary outcome; Production; Progress Reports; prospective; prototype; Provider; Reporting; Research; Research Personnel; Resolution; Risk; Sample Size; Sampling; Sensitivity and Specificity; Signal Transduction; software systems; Specialist; Strategic Planning; Stroke; Structure; success; System; Technology; Time; tool; Training; Transportation; Ultrasonography; United States; Validation; Video Recording; Weight; wireless communication; Wireless Technology