The Experts below are selected from a list of 10233 Experts worldwide ranked by ideXlab platform
Levi J. Hargrove - One of the best experts on this subject based on the ideXlab platform.
-
Online adaptive neural control of a robotic lower Limb Prosthesis.
Journal of neural engineering, 2018Co-Authors: John A. Spanias, Ann M. Simon, Suzanne B. Finucane, Eric J. Perreault, Levi J. HargroveAbstract:Objective The purpose of this study was to develop and evaluate an adaptive intent recognition algorithm that continuously learns to incorporate a lower Limb amputee's neural information (acquired via electromyography (EMG)) as they ambulate with a robotic leg Prosthesis. Approach We present a powered lower Limb Prosthesis that was configured to acquire the user's neural information and kinetic/kinematic information from embedded mechanical sensors, and identify and respond to the user's intent. We conducted an experiment with eight transfemoral amputees over multiple days. EMG and mechanical sensor data were collected while subjects using a powered knee/ankle Prosthesis completed various ambulation activities such as walking on level ground, stairs, and ramps. Our adaptive intent recognition algorithm automatically transitioned the Prosthesis into the different locomotion modes and continuously updated the user's model of neural data during ambulation. Main results Our proposed algorithm accurately and consistently identified the user's intent over multiple days, despite changing neural signals. The algorithm incorporated 96.31% [0.91%] (mean, [standard error]) of neural information across multiple experimental sessions, and outperformed non-adaptive versions of our algorithm-with a 6.66% [3.16%] relative decrease in error rate. Significance This study demonstrates that our adaptive intent recognition algorithm enables incorporation of neural information over long periods of use, allowing assistive robotic devices to accurately respond to the user's intent with low error rates.
-
intent recognition in a powered lower Limb Prosthesis using time history information
Annals of Biomedical Engineering, 2014Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p < 0.01), when compared to strategies that did not use time history, without reducing intent recognition performance during transitions. These results suggest that including time history information across the gait cycle can enhance locomotion mode intent recognition performance.
-
Intent Recognition in a Powered Lower Limb Prosthesis Using Time History Information
Annals of biomedical engineering, 2013Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p
Andrew Sawers - One of the best experts on this subject based on the ideXlab platform.
-
fall related events in people who are lower Limb Prosthesis users the lived experience
Disability and Rehabilitation, 2021Co-Authors: Janis Kim, Brian J. Hafner, Cody L Mcdonald, Andrew SawersAbstract:To explore lived experiences, and identify common themes as well as vocabulary associated with fall-related events in lower Limb Prosthesis (LLP) users.Five focus groups of LLP users from across th...
-
Fall-related events in people who are lower Limb Prosthesis users: the lived experience.
Disability and rehabilitation, 2021Co-Authors: Janis Kim, Brian J. Hafner, Cody L Mcdonald, Andrew SawersAbstract:PURPOSE To explore lived experiences, and identify common themes as well as vocabulary associated with fall-related events in lower Limb Prosthesis (LLP) users. MATERIALS AND METHODS Five focus groups of LLP users from across the United States were conducted remotely via video or tele-conferencing. Focus group transcripts were coded and analyzed using methods adapted from a grounded theory approach to identify themes. RESULTS Focus group participants (n = 25) described experiences associated with fall-related events that resulted in the identification of six themes: (1) memories of fall-related events are shaped by time and context, (2) location and ground conditions influence whether falls occur, (3) some activities come with more risk, (4) fall-related situations are multi-faceted, and often involve the Prosthesis, (5) how LLP users land, but not the way they go down, tends to vary, and (6) not all falls affect LLP users, but some near-falls do. CONCLUSION Consideration for where LLP users fall, what they are doing when they fall, how they fall, what occurs as a result of a fall, and how well memory of a fall persists may enhance recording and reporting of falls, contribute to development of improved fall risk assessment tools, and inspire the design and function of prosthetic componentry for patient safety.Implications for rehabilitationFalls are a common problem in lower Limb Prosthesis (LLP) users that can lead to adverse health outcomes.Concerns over near falls, not just falls, may merit greater attention from rehabilitation professionals.Elements of the lived experience that appear unique to LLP users include the role of prosthetic fit, function, and comfort in losing and/or recovering balance; as well as the tendency of LLP users to modify rather than stop or avoid activities associated with falls.
-
Strength deficits in lower Limb Prosthesis users: A scoping review.
Prosthetics and orthotics international, 2020Co-Authors: Alex Hewson, Shaquitta Dent, Andrew SawersAbstract:Background:Strength deficits may play a central role in the severity of balance, mobility, and endurance impairments in lower Limb Prosthesis users. A body of literature detailing the scope and spe...
-
Narrowing beam-walking is a clinically feasible approach for assessing balance ability in lower-Limb Prosthesis users.
Journal of rehabilitation medicine, 2018Co-Authors: Andrew Sawers, Brian J. HafnerAbstract:OBJECTIVE Challenging clinical balance tests are needed to expose balance deficits in lower-Limb prost-hesis users. This study examined whether narrowing beam-walking could overcome conceptual and practical limitations identified in fixed-width beam-walking. DESIGN Cross-sectional. PARTICIPANTS Unilateral lower-Limb Prosthesis users. METHODS Participants walked 10 times along a low, narrowing beam. Performance was quantified using the normalized distance walked. Heuristic rules were applied to determine whether the narrowing beam task was "too easy," "too hard," or "appropriately challenging" for each participant. Linear regression and Bland-Altman plots were used to determine whether combinations of the first 5 trials could predict participants' stable beam-walking performance. RESULTS Forty unilateral lower-Limb Prosthesis users participated. Narrowing beam-walking was appropriately challenging for 98% of participants. Performance stabilized for 93% of participants within 5 trials, while 62% were stable across all trials. The mean of trials 3-5 accurately predicted stable performance. CONCLUSION A clinical narrowing beam-walking test is likely to challenge a range of lower-Limb Prosthesis users, have minimal administrative burden, and exhibit no floor or ceiling effects. Narrowing beam-walking is therefore a clinically viable method to evaluate lower-Limb Prosthesis users' balance ability, but requires psychometric testing before it is used to assess fall risk.
-
Validation of the Narrowing Beam Walking Test in Lower Limb Prosthesis Users
Archives of physical medicine and rehabilitation, 2018Co-Authors: Andrew Sawers, Brian J. HafnerAbstract:Abstract Objective To evaluate the content, construct, and discriminant validity of the Narrowing Beam Walking Test (NBWT), a performance-based balance test for lower Limb Prosthesis users. Design Cross-sectional study. Setting Research laboratory and prosthetics clinic. Participants Unilateral transtibial and transfemoral Prosthesis users (N=40). Interventions Not applicable. Main Outcome Measures Content validity was examined by quantifying the percentage of participants receiving maximum or minimum scores (ie, ceiling and floor effects). Convergent construct validity was examined using correlations between participants' NBWT scores and scores or times on existing clinical balance tests regularly administered to lower Limb Prosthesis users. Known-groups construct validity was examined by comparing NBWT scores between groups of participants with different fall histories, amputation levels, amputation etiologies, and functional levels. Discriminant validity was evaluated by analyzing the area under each test's receiver operating characteristic (ROC) curve. Results No minimum or maximum scores were recorded on the NBWT. NBWT scores demonstrated strong correlations (ρ=.70‒.85) with scores/times on performance-based balance tests (timed Up and Go test, Four Square Step Test, and Berg Balance Scale) and a moderate correlation (ρ=.49) with the self-report Activities-specific Balance Confidence scale. NBWT performance was significantly lower among participants with a history of falls ( P =.003), transfemoral amputation ( P =.011), and a lower mobility level ( P .50 (ie, chance). Conclusions The results provide strong evidence of content, construct, and discriminant validity for the NBWT as a performance-based test of balance ability. The evidence supports its use to assess balance impairments and fall risk in unilateral transtibial and transfemoral Prosthesis users.
Aaron Young - One of the best experts on this subject based on the ideXlab platform.
-
intent recognition in a powered lower Limb Prosthesis using time history information
Annals of Biomedical Engineering, 2014Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p < 0.01), when compared to strategies that did not use time history, without reducing intent recognition performance during transitions. These results suggest that including time history information across the gait cycle can enhance locomotion mode intent recognition performance.
-
Intent Recognition in a Powered Lower Limb Prosthesis Using Time History Information
Annals of biomedical engineering, 2013Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p
Ann M. Simon - One of the best experts on this subject based on the ideXlab platform.
-
Online adaptive neural control of a robotic lower Limb Prosthesis.
Journal of neural engineering, 2018Co-Authors: John A. Spanias, Ann M. Simon, Suzanne B. Finucane, Eric J. Perreault, Levi J. HargroveAbstract:Objective The purpose of this study was to develop and evaluate an adaptive intent recognition algorithm that continuously learns to incorporate a lower Limb amputee's neural information (acquired via electromyography (EMG)) as they ambulate with a robotic leg Prosthesis. Approach We present a powered lower Limb Prosthesis that was configured to acquire the user's neural information and kinetic/kinematic information from embedded mechanical sensors, and identify and respond to the user's intent. We conducted an experiment with eight transfemoral amputees over multiple days. EMG and mechanical sensor data were collected while subjects using a powered knee/ankle Prosthesis completed various ambulation activities such as walking on level ground, stairs, and ramps. Our adaptive intent recognition algorithm automatically transitioned the Prosthesis into the different locomotion modes and continuously updated the user's model of neural data during ambulation. Main results Our proposed algorithm accurately and consistently identified the user's intent over multiple days, despite changing neural signals. The algorithm incorporated 96.31% [0.91%] (mean, [standard error]) of neural information across multiple experimental sessions, and outperformed non-adaptive versions of our algorithm-with a 6.66% [3.16%] relative decrease in error rate. Significance This study demonstrates that our adaptive intent recognition algorithm enables incorporation of neural information over long periods of use, allowing assistive robotic devices to accurately respond to the user's intent with low error rates.
-
intent recognition in a powered lower Limb Prosthesis using time history information
Annals of Biomedical Engineering, 2014Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p < 0.01), when compared to strategies that did not use time history, without reducing intent recognition performance during transitions. These results suggest that including time history information across the gait cycle can enhance locomotion mode intent recognition performance.
-
Intent Recognition in a Powered Lower Limb Prosthesis Using Time History Information
Annals of biomedical engineering, 2013Co-Authors: Aaron Young, Ann M. Simon, Nicholas P. Fey, Levi J. HargroveAbstract:New computerized and powered lower Limb prostheses are being developed that enable amputees to perform multiple locomotion modes. However, current lower Limb Prosthesis controllers are not capable of transitioning these devices automatically and seamlessly between locomotion modes such as level-ground walking, stairs and slopes. The focus of this study was to evaluate different intent recognition interfaces, which if configured properly, may be capable of providing more natural transitions between locomotion modes. Intent recognition can be accomplished using a multitude of different signals from mechanical sensors on the Prosthesis. Since these signals are non-stationary over any given stride, and gait is cyclical, time history information may improve locomotion mode recognition. The authors propose a dynamic Bayesian network classification strategy to incorporate prior sensor information over the gait cycle with current sensor information. Six transfemoral amputees performed locomotion circuits comprising level-ground walking and ascending/descending stairs and ramps using a powered knee and ankle Prosthesis. Using time history reduced steady-state misclassifications by over half (p
Brian J. Hafner - One of the best experts on this subject based on the ideXlab platform.
-
fall related events in people who are lower Limb Prosthesis users the lived experience
Disability and Rehabilitation, 2021Co-Authors: Janis Kim, Brian J. Hafner, Cody L Mcdonald, Andrew SawersAbstract:To explore lived experiences, and identify common themes as well as vocabulary associated with fall-related events in lower Limb Prosthesis (LLP) users.Five focus groups of LLP users from across th...
-
Fall-related events in people who are lower Limb Prosthesis users: the lived experience.
Disability and rehabilitation, 2021Co-Authors: Janis Kim, Brian J. Hafner, Cody L Mcdonald, Andrew SawersAbstract:PURPOSE To explore lived experiences, and identify common themes as well as vocabulary associated with fall-related events in lower Limb Prosthesis (LLP) users. MATERIALS AND METHODS Five focus groups of LLP users from across the United States were conducted remotely via video or tele-conferencing. Focus group transcripts were coded and analyzed using methods adapted from a grounded theory approach to identify themes. RESULTS Focus group participants (n = 25) described experiences associated with fall-related events that resulted in the identification of six themes: (1) memories of fall-related events are shaped by time and context, (2) location and ground conditions influence whether falls occur, (3) some activities come with more risk, (4) fall-related situations are multi-faceted, and often involve the Prosthesis, (5) how LLP users land, but not the way they go down, tends to vary, and (6) not all falls affect LLP users, but some near-falls do. CONCLUSION Consideration for where LLP users fall, what they are doing when they fall, how they fall, what occurs as a result of a fall, and how well memory of a fall persists may enhance recording and reporting of falls, contribute to development of improved fall risk assessment tools, and inspire the design and function of prosthetic componentry for patient safety.Implications for rehabilitationFalls are a common problem in lower Limb Prosthesis (LLP) users that can lead to adverse health outcomes.Concerns over near falls, not just falls, may merit greater attention from rehabilitation professionals.Elements of the lived experience that appear unique to LLP users include the role of prosthetic fit, function, and comfort in losing and/or recovering balance; as well as the tendency of LLP users to modify rather than stop or avoid activities associated with falls.
-
Narrowing beam-walking is a clinically feasible approach for assessing balance ability in lower-Limb Prosthesis users.
Journal of rehabilitation medicine, 2018Co-Authors: Andrew Sawers, Brian J. HafnerAbstract:OBJECTIVE Challenging clinical balance tests are needed to expose balance deficits in lower-Limb prost-hesis users. This study examined whether narrowing beam-walking could overcome conceptual and practical limitations identified in fixed-width beam-walking. DESIGN Cross-sectional. PARTICIPANTS Unilateral lower-Limb Prosthesis users. METHODS Participants walked 10 times along a low, narrowing beam. Performance was quantified using the normalized distance walked. Heuristic rules were applied to determine whether the narrowing beam task was "too easy," "too hard," or "appropriately challenging" for each participant. Linear regression and Bland-Altman plots were used to determine whether combinations of the first 5 trials could predict participants' stable beam-walking performance. RESULTS Forty unilateral lower-Limb Prosthesis users participated. Narrowing beam-walking was appropriately challenging for 98% of participants. Performance stabilized for 93% of participants within 5 trials, while 62% were stable across all trials. The mean of trials 3-5 accurately predicted stable performance. CONCLUSION A clinical narrowing beam-walking test is likely to challenge a range of lower-Limb Prosthesis users, have minimal administrative burden, and exhibit no floor or ceiling effects. Narrowing beam-walking is therefore a clinically viable method to evaluate lower-Limb Prosthesis users' balance ability, but requires psychometric testing before it is used to assess fall risk.
-
Validation of the Narrowing Beam Walking Test in Lower Limb Prosthesis Users
Archives of physical medicine and rehabilitation, 2018Co-Authors: Andrew Sawers, Brian J. HafnerAbstract:Abstract Objective To evaluate the content, construct, and discriminant validity of the Narrowing Beam Walking Test (NBWT), a performance-based balance test for lower Limb Prosthesis users. Design Cross-sectional study. Setting Research laboratory and prosthetics clinic. Participants Unilateral transtibial and transfemoral Prosthesis users (N=40). Interventions Not applicable. Main Outcome Measures Content validity was examined by quantifying the percentage of participants receiving maximum or minimum scores (ie, ceiling and floor effects). Convergent construct validity was examined using correlations between participants' NBWT scores and scores or times on existing clinical balance tests regularly administered to lower Limb Prosthesis users. Known-groups construct validity was examined by comparing NBWT scores between groups of participants with different fall histories, amputation levels, amputation etiologies, and functional levels. Discriminant validity was evaluated by analyzing the area under each test's receiver operating characteristic (ROC) curve. Results No minimum or maximum scores were recorded on the NBWT. NBWT scores demonstrated strong correlations (ρ=.70‒.85) with scores/times on performance-based balance tests (timed Up and Go test, Four Square Step Test, and Berg Balance Scale) and a moderate correlation (ρ=.49) with the self-report Activities-specific Balance Confidence scale. NBWT performance was significantly lower among participants with a history of falls ( P =.003), transfemoral amputation ( P =.011), and a lower mobility level ( P .50 (ie, chance). Conclusions The results provide strong evidence of content, construct, and discriminant validity for the NBWT as a performance-based test of balance ability. The evidence supports its use to assess balance impairments and fall risk in unilateral transtibial and transfemoral Prosthesis users.
-
A study to assess whether fixed-width beam walking provides sufficient challenge to assess balance ability across lower Limb Prosthesis users.
Clinical rehabilitation, 2017Co-Authors: Andrew Sawers, Brian J. HafnerAbstract:Objective:To evaluate the feasibility of fixed-width beam walking for assessing balance in lower Limb Prosthesis users.Design:Cross-sectional.Setting:Laboratory.Subjects:Lower Limb Prosthesis users.Methods:Participants attempted 10 walking trials on three fixed-width beams (18.6, 8.60, and 4.01 wide; 5.5 m long; 3.8 cm high).Main measures:Beam-walking performance was quantified using the distance walked to balance failure. Heuristic rules applied to each participant’s beam-walking distance to classify each beam as “too easy,” “too hard,” or “appropriately challenging” and determine whether any single beam provided an appropriate challenge to all participants. The number of trials needed to achieve stable beam-walking performance was quantified for appropriately challenging beams by identifying the last inflection point in the slope of each participant’s trial-by-trial cumulative performance record.Results:In all, 30 unilateral lower Limb Prosthesis users participated in the study. Each of the fixed-width ...