Abstract: Anatomical structures such as the musculoskeletal structure of a knee or hip joint, are modeled using a predictive cause-and-effect mathematical model wherein parameters and interactions associated with biological tissues are examined. The model extends over nested small scale parameters (e.g., genetic or cellular) up to macro scale parameters, e.g., body force and motion. The parameter values are populated for a subject or group, and the model is operated iteratively while subjecting the parameters to one or more influences, to project changes over a span of time that encompasses adaptive changes in tissues and also aging and wear.

Abstract: A biophysical virtual model of a body or body section of a human subject contains measured parameter values, scan data and images from surface or full body imaging systems, and also descriptive and subject identification data. Data in the model are applied to customize external objects ergonomically to fit a subject, by adjustment or by selection when the objects are configured for one or a group of subjects. The database can be centralized and/or mobile devices carried by users can supply model data to external apparatus. Where a parameter value needed for a subject is unknown, the statistical distribution of the database and the correlation of parameters can supply a probable value and level of certainty. In connection with values that are known for an individual, complexities inherent in the combination of plural parameters can be collected in the model and used in later security screens to confirm the identity of a subject.