Vikram Aggarwal

Summary

Affiliation: Johns Hopkins University
Country: USA

Publications

  1. pmc State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements
    Vikram Aggarwal
    Dept of Biomedical Engineering, Johns Hopkins Univ, Baltimore, MD, USA
    J Neurophysiol 109:3067-81. 2013
  2. ncbi request reprint Ultrasound-guided noninvasive measurement of a patient's central venous pressure
    Vikram Aggarwal
    Dept of Biomed Eng, Johns Hopkins Univ, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 1:3843-9. 2006
  3. doi request reprint Towards closed-loop decoding of dexterous hand movements using a virtual integration environment
    Vikram Aggarwal
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:1703-6. 2008
  4. pmc Cortical decoding of individual finger and wrist kinematics for an upper-limb neuroprosthesis
    Vikram Aggarwal
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2009:4535-8. 2009
  5. pmc Decoding individuated finger movements using volume-constrained neuronal ensembles in the M1 hand area
    Soumyadipta Acharya
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
    IEEE Trans Neural Syst Rehabil Eng 16:15-23. 2008
  6. pmc Asynchronous decoding of dexterous finger movements using M1 neurons
    Vikram Aggarwal
    Department of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
    IEEE Trans Neural Syst Rehabil Eng 16:3-14. 2008
  7. pmc Spatiotemporal variation of multiple neurophysiological signals in the primary motor cortex during dexterous reach-to-grasp movements
    Mohsen Mollazadeh
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205, USA
    J Neurosci 31:15531-43. 2011
  8. doi request reprint Spectral modulation of LFP activity in M1 during dexterous finger movements
    Mohsen Mollazadeh
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:5314-7. 2008
  9. pmc Identifying neuron communities during a reach and grasp task using an unsupervised clustering analysis
    Geoffrey I Newman
    Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2011:6401-4. 2011
  10. pmc A brain-computer interface with vibrotactile biofeedback for haptic information
    Aniruddha Chatterjee
    Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
    J Neuroeng Rehabil 4:40. 2007

Detail Information

Publications10

  1. pmc State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements
    Vikram Aggarwal
    Dept of Biomedical Engineering, Johns Hopkins Univ, Baltimore, MD, USA
    J Neurophysiol 109:3067-81. 2013
    ..67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation...
  2. ncbi request reprint Ultrasound-guided noninvasive measurement of a patient's central venous pressure
    Vikram Aggarwal
    Dept of Biomed Eng, Johns Hopkins Univ, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 1:3843-9. 2006
    ..The measurement procedure is also simple enough to be performed by operators without extensive medical training...
  3. doi request reprint Towards closed-loop decoding of dexterous hand movements using a virtual integration environment
    Vikram Aggarwal
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:1703-6. 2008
    ..This work lays the foundation for future closed-loop experiments with monkeys in the loop and dexterous control of an actual prosthetic limb...
  4. pmc Cortical decoding of individual finger and wrist kinematics for an upper-limb neuroprosthesis
    Vikram Aggarwal
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2009:4535-8. 2009
    ..58-0.81, 0.05-0.07). These results suggest that individual finger and wrist kinematics can be decoded with high accuracy, and be used to control a multi-fingered prosthetic hand in real-time...
  5. pmc Decoding individuated finger movements using volume-constrained neuronal ensembles in the M1 hand area
    Soumyadipta Acharya
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
    IEEE Trans Neural Syst Rehabil Eng 16:15-23. 2008
    ..The results suggest that a brain-machine interface (BMI) for dexterous control of individuated fingers and the wrist can be implemented using microelectrode arrays placed broadly in the M1 hand area...
  6. pmc Asynchronous decoding of dexterous finger movements using M1 neurons
    Vikram Aggarwal
    Department of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
    IEEE Trans Neural Syst Rehabil Eng 16:3-14. 2008
    ..This work takes an important step towards the development of a BMI for direct neural control of a state-of-the-art, multifingered hand prosthesis...
  7. pmc Spatiotemporal variation of multiple neurophysiological signals in the primary motor cortex during dexterous reach-to-grasp movements
    Mohsen Mollazadeh
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205, USA
    J Neurosci 31:15531-43. 2011
    ....
  8. doi request reprint Spectral modulation of LFP activity in M1 during dexterous finger movements
    Mohsen Mollazadeh
    Department of Biomedical Engineering at the Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:5314-7. 2008
    ..This has implications for future neuroprosthetic devices due to the robustness of LFP signals for chronic recording...
  9. pmc Identifying neuron communities during a reach and grasp task using an unsupervised clustering analysis
    Geoffrey I Newman
    Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
    Conf Proc IEEE Eng Med Biol Soc 2011:6401-4. 2011
    ..73) than using randomly selected neurons (r=0.68). This suggests that the proposed method can be used to prune the input space and identify an optimal population of neurons for BMI tasks...
  10. pmc A brain-computer interface with vibrotactile biofeedback for haptic information
    Aniruddha Chatterjee
    Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
    J Neuroeng Rehabil 4:40. 2007
    ..Operation of an EEG-based BCI using only vibrotactile feedback, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy...