Comprehensive, Quantitative, Predictive Model of the Human  Knee Joint
{'Code': '07020000', 'Directorate': {'LongName': 'Directorate For Engineering'}, 'Division': {'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'william weigand'}
This research will involve the development of a model of the human knee         joint which will allow quantitative and predictive analyses of normal           and pathological knees.  The model will be validated by measurements on         cadaverous material and by experiments on people.  The dynamic                  predictive capability of the knee model will be evaluated using                 optimization analyses of the lower extremity musculoskeletal model              during gait to establish the time course and force level of the                 individual muscles as compared to synchronously acquired myoelectric            signals.  The model will allow study of the normal and pathological             knee joint's dynamic and kinematic properties.  In this way, it will            contribute to the prevention and treatment of knee joint injuries and           will aid in the design of knee prostheses.
{'FirstName': 'Robert', 'LastName': 'Mann', 'EmailAddress': None, 'StartDate': '10/01/1985', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'Cambridge', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA'}
{'Code': '5342', 'Text': 'Disability & Rehab Engineering'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1984&All=true', 'xml': '8415430.xml'}