@Article{Bonnet2015,
  Title                    = {Fast Determination of the Planar Body Segment Inertial Parameters Using Affordable Sensors},
  Author                   = {Bonnet, V. and Venture, G.},
  Journal                  = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  Year                     = {2015},
  Pages                    = {628--635},
  Volume                   = {23},

  Abstract                 = {This study aimed at developing and evaluating a new method for the fast and reliable identification of body segment inertial parameters with a planar model using affordable sensors. A Kinect sensor, with a new marker-based tracking system, and a Wii balance board were used as an affordable and portable motion capture system. A set of optimal exciting motions was used in a biofeedback interface to identify the body segment parameters. The method was validated with 12 subjects performing various standardized motions. The same dynamometric quantities estimated both with the proposed system and, as a reference, with a laboratory grade force-plate were compared. The results showed that the proposed method could successfully estimate the resultant moment and the vertical ground reaction force (rms errors less than 8 Nm and 12 N, respectively). Finally, when local segment values were artificially varied, the proposed method was able to detect and estimate the additional masses accurately and with an error of less than 0.5 Kg, contrary to values generated with commonly used anthropometric tables.},
  Doi                      = {10.1109/TNSRE.2015.2405087},
  ISSN                     = {1534-4320},
  Keywords                 = {Joints;Kinetic theory;Mathematical model;Robots;Sensors;Tracking;Visualization;Body segment inertial parameters;identification;inverse dynamics},
  Review                   = {3 step system:
- set up the forward model (standard robotics equn -> regressor matrix)
- set up optimal exciting motion by setting a given joint to excite, and they generate the movements of the other joints via Fourier series (so there's a way to generate the joints)
- optimize, to minimize the error between the forward model and the measured force and coupling matrix (eqn 12)},
  Timestamp                = {2015.07.09}
}

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A Kinect sensor, with a new marker-based tracking system, and a Wii balance board were used as an affordable and portable motion capture system. A set of optimal exciting motions was used in a biofeedback interface to identify the body segment parameters. The method was validated with 12 subjects performing various standardized motions. The same dynamometric quantities estimated both with the proposed system and, as a reference, with a laboratory grade force-plate were compared. The results showed that the proposed method could successfully estimate the resultant moment and the vertical ground reaction force (rms errors less than 8 Nm and 12 N, respectively). Finally, when local segment values were artificially varied, the proposed method was able to detect and estimate the additional masses accurately and with an error of less than 0.5 Kg, contrary to values generated with commonly used anthropometric tables.","doi":"10.1109/TNSRE.2015.2405087","issn":"1534-4320","keywords":"Joints;Kinetic theory;Mathematical model;Robots;Sensors;Tracking;Visualization;Body segment inertial parameters;identification;inverse dynamics","review":"3 step system: - set up the forward model (standard robotics equn -> regressor matrix) - set up optimal exciting motion by setting a given joint to excite, and they generate the movements of the other joints via Fourier series (so there's a way to generate the joints) - optimize, to minimize the error between the forward model and the measured force and coupling matrix (eqn 12)","timestamp":"2015.07.09","bibtex":"@Article{Bonnet2015,\n Title = {Fast Determination of the Planar Body Segment Inertial Parameters Using Affordable Sensors},\n Author = {Bonnet, V. and Venture, G.},\n Journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},\n Year = {2015},\n Pages = {628--635},\n Volume = {23},\n\n Abstract = {This study aimed at developing and evaluating a new method for the fast and reliable identification of body segment inertial parameters with a planar model using affordable sensors. A Kinect sensor, with a new marker-based tracking system, and a Wii balance board were used as an affordable and portable motion capture system. A set of optimal exciting motions was used in a biofeedback interface to identify the body segment parameters. The method was validated with 12 subjects performing various standardized motions. The same dynamometric quantities estimated both with the proposed system and, as a reference, with a laboratory grade force-plate were compared. The results showed that the proposed method could successfully estimate the resultant moment and the vertical ground reaction force (rms errors less than 8 Nm and 12 N, respectively). Finally, when local segment values were artificially varied, the proposed method was able to detect and estimate the additional masses accurately and with an error of less than 0.5 Kg, contrary to values generated with commonly used anthropometric tables.},\n Doi = {10.1109/TNSRE.2015.2405087},\n ISSN = {1534-4320},\n Keywords = {Joints;Kinetic theory;Mathematical model;Robots;Sensors;Tracking;Visualization;Body segment inertial parameters;identification;inverse dynamics},\n Review = {3 step system:\n- set up the forward model (standard robotics equn -> regressor matrix)\n- set up optimal exciting motion by setting a given joint to excite, and they generate the movements of the other joints via Fourier series (so there's a way to generate the joints)\n- optimize, to minimize the error between the forward model and the measured force and coupling matrix (eqn 12)},\n Timestamp = {2015.07.09}\n}\n\n","author_short":["Bonnet, V.","Venture, G."],"key":"Bonnet2015","id":"Bonnet2015","bibbaseid":"bonnet-venture-fastdeterminationoftheplanarbodysegmentinertialparametersusingaffordablesensors-2015","role":"author","urls":{},"keyword":["Joints;Kinetic theory;Mathematical model;Robots;Sensors;Tracking;Visualization;Body segment inertial parameters;identification;inverse dynamics"],"downloads":0},"search_terms":["fast","determination","planar","body","segment","inertial","parameters","using","affordable","sensors","bonnet","venture"],"keywords":["joints;kinetic theory;mathematical model;robots;sensors;tracking;visualization;body segment inertial parameters;identification;inverse dynamics"],"authorIDs":[],"dataSources":["iCsmKnycRmHPxmhBd"]}