Continuous A-Mode Ultrasound-Based Prediction of Transfemoral Amputee Prosthesis Kinematics Across Different Ambulation Tasks

Details

• Alternative Title:
  IEEE Trans Biomed Eng
• Personal Author:
  Mendez, Joel ; Murray, Rosemarie ; Gabert, Lukas ; Fey, Nicholas P. ; Liu, Honghai ; Lenzi, Tommaso
• Description:
  Objective:
  
  Volitional control systems for powered prostheses require the detection of user intent to operate in real life scenarios. Ambulation mode classification has been proposed to address this issue. However, these approaches introduce discrete labels to the otherwise continuous task that is ambulation. An alternative approach is to provide users with direct, voluntary control of the powered prosthesis motion. Surface electromyography (EMG) sensors have been proposed for this task, but poor signal-to-noise ratios and crosstalk from neighboring muscles limit performance. B-mode ultrasound can address some of these issues at the cost of reduced clinical viability due to the substantial increase in size, weight, and cost. Thus, there is an unmet need for a lightweight, portable neural system that can effectively detect the movement intention of individuals with lower-limb amputation.
  
  Methods:
  
  In this study, we show that a small and lightweight A-mode ultrasound system can continuously predict prosthesis joint kinematics in seven individuals with transfemoral amputation across different ambulation tasks. Features from the A-mode ultrasound signals were mapped to the user’s prosthesis kinematics via an artificial neural network.
  
  Results:
  
  Predictions on testing ambulation circuit trials resulted in a mean normalized RMSE across different ambulation modes of 8.7 ± 3.1%, 4.6 ± 2.5%, 7.2 ± 1.8%, and 4.6 ± 2.4% for knee position, knee velocity, ankle position, and ankle velocity, respectively.
  
  Conclusion and Significance:
  
  This study lays the foundation for future applications of A-mode ultrasound for volitional control of powered prostheses during a variety of daily ambulation tasks.
  
  
• Subjects:
  Amputees Artificial Limbs Biomechanical Phenomena Electromyography Humans Walking
• Keywords:
  A-Mode Ultrasound Intent Recognition Joint Kinematics Prediction Lower-limb Prosthesis Transfemoral Amputation
• Source:
  IEEE Trans Biomed Eng. 71(1):56-67
• Pubmed ID:
  37428665
• Pubmed Central ID:
  PMC10900992
• Document Type:
  Journal Article
• Funding:
  R01 HD098154/HD/NICHD NIH HHSUnited States/ ; T32 TR004394/TR/NCATS NIH HHSUnited States/ ; UL1 TR002538/TR/NCATS NIH HHSUnited States/ ; T42 OH008414/OH/NIOSH CDC HHSUnited States/
• Volume:
  71
• Issue:
  1
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:6666525f3d3c5ab9b6cca6b2baafbb8f842eeffd2a3876f27254b526778e40f5a1899bd295c68face862a0c92cd50f6c24d22102b14d2840dd1dedc8aa96bb5a
• Download URL:
  https://stacks.cdc.gov/view/cdc/174791/cdc_174791_DS1.pdf
• File Type:
  [PDF - 1.11 MB ]