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Timothy Mastroianni - One of the best experts on this subject based on the ideXlab platform.

  • ICMLA - Implementation of a Smartphone as a Wearable and Wireless Gyroscope Platform for Machine Learning Classification of Hemiplegic Gait Through a Multilayer Perceptron Neural Network
    2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The smartphone represents a wearable and wireless system with the potential to have transformative influence on the biomedical and healthcare industry. An intrinsic feature of the smartphone is a gyroscope sensor, for which with a software application the smartphone functions as a wearable and wireless gyroscope platform. The resultant gyroscope data recording presents a clinical recognizable signal, which has been successful demonstrated to quantify aspects of human movement characteristics, such as the patellar tendon reflex. Gait another associated feature of human movement can be readily quantified by a smartphone functioning as a wearable and wireless gyroscope platform. The research objective is to distinguish between an affected leg and unaffected leg during Hemiplegic Gait based on a smartphone functioning as a wearable and wireless gyroscope platform though machine learning classification. A single smartphone is applied to quantify Hemiplegic Gait. The smartphone is first mounted to the affected leg and then the unaffected leg with velocity constrained to a constant velocity by a treadmill. Through wireless connectivity to the Internet the gyroscope signal data is conveyed as an email attachment for post-processing at a remote location. Software automation consolidates the gyroscope signal data of Hemiplegic Gait to a feature set for machine learning classification. With the application of a multilayer perceptron neural network considerable classification accuracy is attained for distinguishing between the affected leg and unaffected leg of Hemiplegic Gait. Future implications of the successful implementation of a smartphone as a wearable and wireless gyroscope for machine learning classification of Hemiplegic Gait through a multilayer perceptron neural network elucidate pathways to highly optimized therapy through machine learning with the potential for patients to reside remote from their therapist.

  • IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING Hemiplegic Gait DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT
    Journal of Mechanics in Medicine and Biology, 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy Gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of Hemiplegic Gait from an engineering proof of concept perspective. In order to maintain a consistent Gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the Gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of Gait. Two Gait parameters were obtained: stance-to-stance temporal disparity and stance-to-stance time-averaged acceleration, and demonstrated considerable accuracy, consistency, and reliability. As noted per the constant treadmill velocity, stance-to-stance temporal disparity for the affected and unaffected legs was established as not statistically significant. A statistical significance was determined for the stance-to-stance time-averaged acceleration regarding the affected and unaffected legs. The iPhone application represents a wireless accelerometer platform capable of identifying statistically significant and quantified disparity of Hemiplegic Gait features through automated post-processing in a functionally autonomous environment.

  • IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING Hemiplegic Gait DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT
    Journal of Mechanics in Medicine and Biology, 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy Gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of Hemiplegic Gait from an engineering proof of concept perspective. In order to maintain a consistent Gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the Gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of Gait. Two Gait parameters were obtained: stance-to-st...

  • Implementation of a Smartphone as a Wearable and Wireless Gyroscope Platform for Machine Learning Classification of Hemiplegic Gait Through a Multilayer Perceptron Neural Network
    2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The smartphone represents a wearable and wireless system with the potential to have transformative influence on the biomedical and healthcare industry. An intrinsic feature of the smartphone is a gyroscope sensor, for which with a software application the smartphone functions as a wearable and wireless gyroscope platform. The resultant gyroscope data recording presents a clinical recognizable signal, which has been successful demonstrated to quantify aspects of human movement characteristics, such as the patellar tendon reflex. Gait another associated feature of human movement can be readily quantified by a smartphone functioning as a wearable and wireless gyroscope platform. The research objective is to distinguish between an affected leg and unaffected leg during Hemiplegic Gait based on a smartphone functioning as a wearable and wireless gyroscope platform though machine learning classification. A single smartphone is applied to quantify Hemiplegic Gait. The smartphone is first mounted to the affected leg and then the unaffected leg with velocity constrained to a constant velocity by a treadmill. Through wireless connectivity to the Internet the gyroscope signal data is conveyed as an email attachment for post-processing at a remote location. Software automation consolidates the gyroscope signal data of Hemiplegic Gait to a feature set for machine learning classification. With the application of a multilayer perceptron neural network considerable classification accuracy is attained for distinguishing between the affected leg and unaffected leg of Hemiplegic Gait. Future implications of the successful implementation of a smartphone as a wearable and wireless gyroscope for machine learning classification of Hemiplegic Gait through a multilayer perceptron neural network elucidate pathways to highly optimized therapy through machine learning with the potential for patients to reside remote from their therapist.

  • Portable Wearable and Wireless Systems for Gait and Reflex Response Quantification
    Smart Sensors Measurement and Instrumentation, 2017
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    With the advent of wireless technology and inertial measurement units, the prevalence of wireless accelerometers is addressed for quantification of Gait, reflex response, and reflex latency. Over the course of four generations of research, development, testing, and evaluation the ability to quantify patellar tendon reflex response and latency has been achieved in an accurate, reliable, and reproducible manner. As a transitional phase to the research, development, testing, and evaluation cycle an artificial reflex device was also applied. The central themes to the wireless quantified reflex device are tandem operated wireless accelerometer nodes that are effectively wearable for deriving response and latency and a potential energy impact pendulum for evoking the patellar tendon reflex. The successful application of these wireless accelerometers that are wearable has been further extended toward the quantification of Hemiplegic Gait, and real-time modification of Hemiplegic Gait through the quantified feedback of Virtual Proprioception. Other developments regarding the use of wireless accelerometers that are wearable are further addressed.

Sarah F Tyson - One of the best experts on this subject based on the ideXlab platform.

  • The effect of a slider shoe on Hemiplegic Gait
    Clinical Rehabilitation, 2020
    Co-Authors: J Cross, Sarah F Tyson
    Abstract:

    Objective: To assess the effect of a slider shoe on the Gait speed and energy efficiency of Hemiplegic Gait.Design: A–B–A single-case design to compare walking with and without the slider shoe. Results were assessed graphically using the 2SD method.Setting: Stroke unit of an NHS general hospital in the UK.Subjects: Four acute stroke patients undergoing Gait rehabilitation.Intervention: Walking practice with and without a slider shoe worn over the real shoe of the weak leg.Main outcome measures: Gait speed (10-m walk test) and energy efficiency (Physiological Cost Index).Results: All subjects showed an improvement in speed and efficiency when wearing the slider shoe compared with the baseline phase (A1). Three subjects showed a sustained improvement in efficiency and two showed a sustained improvement in speed in the second baseline phase (A2).Conclusion: A slider shoe may improve the speed and efficiency of Hemiplegic Gait for people in the early stages of Gait rehabilitation. Further investigation is war...

  • Effect of a Hinged Ankle Foot Orthosis on Hemiplegic Gait
    Physiotherapy, 2000
    Co-Authors: Sarah F Tyson, H Thornton
    Abstract:

    Subjects and setting Twenty-five subjects over 18 years, with hemiplegia following CVA undergoing rehabilitation in a regional rehabilitation unit. Outcome measures Functional ambulation categories as a measure of disability. Paper walkways to measure Gait impairments – stride length, step length, symmetry, cadence and velocity. Face-to-face questionnaire to determine the users’ opinion of the hinged AFO.

  • trunk kinematics in Hemiplegic Gait and the effect of walking aids
    Clinical Rehabilitation, 1999
    Co-Authors: Sarah F Tyson
    Abstract:

    Objective: To establish baseline measurements of trunk movements during Hemiplegic Gait, to assess the relationship between trunk movements and walking ability, and to investigate the effect of walking aids on the trunk movements.Method: Twenty subjects with a chronic hemiplegia from a stroke, who could walk independently, were recruited. Lateral and vertical movements of the pelvis, and symmetry of these movements were measured using CODA (a three-dimensional movement analysis system) as the subjects walked at their own pace without an aid. They were also tested as they walked with a stick and a tripod to assess the effect of different walking aids. Mean values for the trunk movements and symmetry were calculated, Pearson's correlations assessed the relationship between each trunk movement and Gait velocity (a measure of overall walking ability), and the influence of the different aids was assessed using a one-way repeated measures ANOVA.Results: Lateral displacement was large (mean = 9.9 cm, SD 3.9) and...

  • the effect of a hinged ankle foot orthosis on Hemiplegic Gait four single case studies
    Physiotherapy Theory and Practice, 1998
    Co-Authors: Sarah F Tyson, H Thornton, Andrew Downes
    Abstract:

    This study used a single-case design to assess the effect of a hinged ankle-foot orthosis (AFO) on four Hemiplegic subjects, and elicited their views of the AFO. The Gait parameters measured were: velocity, stride length, step length and symmetry using a paper walkway. The subjects walked without (phase A) and then with (phase B) the AFO. The subjects' views were sought using a semi-structured questionnaire. The data were displayed graphically and analysed using autocorrelations and paired t-tests to compare phases A and B in each parameter for each subject. All subjects showed significant improvements in velocity, stride and step length in the sound and weak legs, and three of the subjects showed significant improvements in symmetry. The subjects all viewed the AFO positively and felt that it improved their walking. They placed more emphasis on the changes in disability than impairment.

  • the support taken through walking aids during Hemiplegic Gait
    Clinical Rehabilitation, 1998
    Co-Authors: Sarah F Tyson
    Abstract:

    Objective: To assess the effect of different aids on the amount of support Hemiplegic subjects took from them. The relationship between the amount of support, severity of hemiplegia and walking ability were also assessed.Design: Hemiplegic subjects' Gait and the amount of support they took from the aid were measured as they walked with a normal height stick, a high stick and a tripod.Subjects: Fifteen subjects with a hemiplegia of more than three months' duration who could walk independently were recruited.Outcome measures: Velocity, the gross function section of the Rivermead Motor Assessment, percentage bodyweight taken through the aid, the aid contact time, the placement of the aid, and the lateral shift of the pelvis when weight bearing were assessed.Results: No differences in the amount of support or walking ability were found with the different aids. There was a significant relationship between severity of hemiplegia and the percentage of bodyweight taken through the aid (r = –0.67), between aid con...

Robert Lemoyne - One of the best experts on this subject based on the ideXlab platform.

  • ICMLA - Implementation of a Smartphone as a Wearable and Wireless Gyroscope Platform for Machine Learning Classification of Hemiplegic Gait Through a Multilayer Perceptron Neural Network
    2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The smartphone represents a wearable and wireless system with the potential to have transformative influence on the biomedical and healthcare industry. An intrinsic feature of the smartphone is a gyroscope sensor, for which with a software application the smartphone functions as a wearable and wireless gyroscope platform. The resultant gyroscope data recording presents a clinical recognizable signal, which has been successful demonstrated to quantify aspects of human movement characteristics, such as the patellar tendon reflex. Gait another associated feature of human movement can be readily quantified by a smartphone functioning as a wearable and wireless gyroscope platform. The research objective is to distinguish between an affected leg and unaffected leg during Hemiplegic Gait based on a smartphone functioning as a wearable and wireless gyroscope platform though machine learning classification. A single smartphone is applied to quantify Hemiplegic Gait. The smartphone is first mounted to the affected leg and then the unaffected leg with velocity constrained to a constant velocity by a treadmill. Through wireless connectivity to the Internet the gyroscope signal data is conveyed as an email attachment for post-processing at a remote location. Software automation consolidates the gyroscope signal data of Hemiplegic Gait to a feature set for machine learning classification. With the application of a multilayer perceptron neural network considerable classification accuracy is attained for distinguishing between the affected leg and unaffected leg of Hemiplegic Gait. Future implications of the successful implementation of a smartphone as a wearable and wireless gyroscope for machine learning classification of Hemiplegic Gait through a multilayer perceptron neural network elucidate pathways to highly optimized therapy through machine learning with the potential for patients to reside remote from their therapist.

  • IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING Hemiplegic Gait DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT
    Journal of Mechanics in Medicine and Biology, 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy Gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of Hemiplegic Gait from an engineering proof of concept perspective. In order to maintain a consistent Gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the Gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of Gait. Two Gait parameters were obtained: stance-to-stance temporal disparity and stance-to-stance time-averaged acceleration, and demonstrated considerable accuracy, consistency, and reliability. As noted per the constant treadmill velocity, stance-to-stance temporal disparity for the affected and unaffected legs was established as not statistically significant. A statistical significance was determined for the stance-to-stance time-averaged acceleration regarding the affected and unaffected legs. The iPhone application represents a wireless accelerometer platform capable of identifying statistically significant and quantified disparity of Hemiplegic Gait features through automated post-processing in a functionally autonomous environment.

  • IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING Hemiplegic Gait DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT
    Journal of Mechanics in Medicine and Biology, 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy Gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of Hemiplegic Gait from an engineering proof of concept perspective. In order to maintain a consistent Gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the Gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of Gait. Two Gait parameters were obtained: stance-to-st...

  • Implementation of a Smartphone as a Wearable and Wireless Gyroscope Platform for Machine Learning Classification of Hemiplegic Gait Through a Multilayer Perceptron Neural Network
    2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    The smartphone represents a wearable and wireless system with the potential to have transformative influence on the biomedical and healthcare industry. An intrinsic feature of the smartphone is a gyroscope sensor, for which with a software application the smartphone functions as a wearable and wireless gyroscope platform. The resultant gyroscope data recording presents a clinical recognizable signal, which has been successful demonstrated to quantify aspects of human movement characteristics, such as the patellar tendon reflex. Gait another associated feature of human movement can be readily quantified by a smartphone functioning as a wearable and wireless gyroscope platform. The research objective is to distinguish between an affected leg and unaffected leg during Hemiplegic Gait based on a smartphone functioning as a wearable and wireless gyroscope platform though machine learning classification. A single smartphone is applied to quantify Hemiplegic Gait. The smartphone is first mounted to the affected leg and then the unaffected leg with velocity constrained to a constant velocity by a treadmill. Through wireless connectivity to the Internet the gyroscope signal data is conveyed as an email attachment for post-processing at a remote location. Software automation consolidates the gyroscope signal data of Hemiplegic Gait to a feature set for machine learning classification. With the application of a multilayer perceptron neural network considerable classification accuracy is attained for distinguishing between the affected leg and unaffected leg of Hemiplegic Gait. Future implications of the successful implementation of a smartphone as a wearable and wireless gyroscope for machine learning classification of Hemiplegic Gait through a multilayer perceptron neural network elucidate pathways to highly optimized therapy through machine learning with the potential for patients to reside remote from their therapist.

  • Portable Wearable and Wireless Systems for Gait and Reflex Response Quantification
    Smart Sensors Measurement and Instrumentation, 2017
    Co-Authors: Robert Lemoyne, Timothy Mastroianni
    Abstract:

    With the advent of wireless technology and inertial measurement units, the prevalence of wireless accelerometers is addressed for quantification of Gait, reflex response, and reflex latency. Over the course of four generations of research, development, testing, and evaluation the ability to quantify patellar tendon reflex response and latency has been achieved in an accurate, reliable, and reproducible manner. As a transitional phase to the research, development, testing, and evaluation cycle an artificial reflex device was also applied. The central themes to the wireless quantified reflex device are tandem operated wireless accelerometer nodes that are effectively wearable for deriving response and latency and a potential energy impact pendulum for evoking the patellar tendon reflex. The successful application of these wireless accelerometers that are wearable has been further extended toward the quantification of Hemiplegic Gait, and real-time modification of Hemiplegic Gait through the quantified feedback of Virtual Proprioception. Other developments regarding the use of wireless accelerometers that are wearable are further addressed.

Ole Kaeseler Andersen - One of the best experts on this subject based on the ideXlab platform.

  • A novel method exploiting the nociceptive withdrawal reflexes in rehabilitation of Hemiplegic Gait
    IFMBE Proceedings, 2020
    Co-Authors: Jonas Emborg, Erika G Spaich, Jan Dimon Bendtsen, Ole Kaeseler Andersen
    Abstract:

    A novel closed loop method for improving Gait in Hemiplegic patients by supporting the production of the swing phase using electrical stimulations to evoke the nociceptive withdrawal reflex was developed and evaluated in one chronic Hemiplegic subject. Electrical stimulations were delivered to 4 locations on the sole of the foot at 3 different times between heel-off and toe-off. The system exploits the modular organization of the nociceptive withdrawal reflex and its stimulation site- and Gait phase-modulation in order to evoke optimal flexion of the hip, knee and ankle joints in the early swing phase. A Rule-based Model Reference Adaptive Controller (MRAC) was designed to select the optimal stimulation parameters. It was hypothesized that the MRAC-system would result in a better walking pattern compared with a preprogrammed fixed stimulation pattern controller. Based on the unperturbed Gait and withdrawal strategies of the patient, an individual controller target for hip, knee and ankle flexion was set. The patient walked 10 min with the MRAC-system, 10 min with the fixed pre-programmed stimulation pattern, and 10 min with no-stimulation. The results indicate that both stimulation paradigms resulted in a more functional Gait compared with no-stimulation and that the control strategy in the MRAC system is superior suggesting that it will be able to adapt better to the varying needs during rehabilitation therapy.

  • EXPLOITING THE NOCICEPTIVE WITHDRAWAL REFLEXES IN REHABILITATION OF Hemiplegic Gait: A CASE STUDY
    2020
    Co-Authors: Jonas Emborg, Erika G Spaich, Jan Dimon Bendtsen, Zlatko Matjacic, Imre Cikajlo, Nika Goljar, Ole Kaeseler Andersen
    Abstract:

    Background: A closed loop system for improving Gait in Hemiplegic patients by supporting the production of the swing phase using electrical stimulations evoking the nociceptive withdrawal reflex was designed and evaluated in one chronic Hemiplegic subject. Methods: Electrical stimulations were delivered to 4 locations on the sole of the foot at 3 different time points between heel-off and toe-off. The system exploits the modular organization of the nociceptive withdrawal reflex and its site and phase modulation during Gait in order evoke optimal flexion of the hip, knee and ankle joints in early swing phase. A Model Reference Adaptive Controller (MRAC) was designed to select the optimal stimulation parameters. The hypothesis was that the MRAC-system result in better walking pattern compared with a preprogrammed fixed pattern controller. Based on the patient unperturbed Gait and his withdrawal strategies an individual controller target for hip, knee and ankle flexion were set. The patient walked 10 min with the MRAC-system, 10 min with the fixed pre-programmed pattern and 10 min with no-stimulation.

  • modulation of the withdrawal reflex during Hemiplegic Gait effect of stimulation site and Gait phase
    Clinical Neurophysiology, 2006
    Co-Authors: Erika G Spaich, H H Hinge, Lars Arendtnielsen, Ole Kaeseler Andersen
    Abstract:

    OBJECTIVE: The objective of the study was to investigate the sensitivity of the nociceptive withdrawal reflex to stimulation of different locations on the sole of the foot during Hemiplegic Gait. METHODS: Reflexes were evoked by cutaneous electrical stimulation of 4 locations on the sole of the foot of 7 Hemiplegic and 6 age-matched healthy persons. The stimuli were delivered at heel-contact, during foot-flat, at heel-off, and during mid-swing. Reflexes were recorded from muscles of the stimulated and the contralateral leg. Ankle, knee, and hip joints angles were recorded using goniometers. RESULTS: In the Hemiplegic persons, the size of tibialis anterior reflexes, and the latency of soleus reflexes were site- and phase-modulated. In both groups, the tibialis anterior reflexes were significantly smaller with stimulation to the fifth metatarsophalangeal joint and the heel compared with the first metatarsophalangeal joint and the arch of the foot. The tibialis anterior reflexes evoked at heel-off and mid-swing were larger in Hemiplegic persons than in healthy persons. Reflexes in the proximal and contralateral limb muscles were not site-modulated during Hemiplegic Gait. The kinematic response at the ankle joint was also different in the two groups during mid-swing. CONCLUSIONS: Hemiplegic and healthy middle-aged people presented different phase-modulation of the kinematic and muscle nociceptive reflex responses evoked by stimulation delivered on the sole of the foot. SIGNIFICANCE: The results have potential application in programs to rehabilitate Hemiplegic Gait.

  • Modulation of the withdrawal reflex during Hemiplegic Gait: effect of stimulation site and Gait phase.
    Clinical Neurophysiology, 2006
    Co-Authors: Erika G Spaich, H H Hinge, Lars Arendt-nielsen, Ole Kaeseler Andersen
    Abstract:

    Abstract Objective The objective of the study was to investigate the sensitivity of the nociceptive withdrawal reflex to stimulation of different locations on the sole of the foot during Hemiplegic Gait. Methods Reflexes were evoked by cutaneous electrical stimulation of 4 locations on the sole of the foot of 7 Hemiplegic and 6 age-matched healthy persons. The stimuli were delivered at heel-contact, during foot-flat, at heel-off, and during mid-swing. Reflexes were recorded from muscles of the stimulated and the contralateral leg. Ankle, knee, and hip joints angles were recorded using goniometers. Results In the Hemiplegic persons, the size of tibialis anterior reflexes, and the latency of soleus reflexes were site- and phase-modulated. In both groups, the tibialis anterior reflexes were significantly smaller with stimulation to the fifth metatarsophalangeal joint and the heel compared with the first metatarsophalangeal joint and the arch of the foot. The tibialis anterior reflexes evoked at heel-off and mid-swing were larger in Hemiplegic persons than in healthy persons. Reflexes in the proximal and contralateral limb muscles were not site-modulated during Hemiplegic Gait. The kinematic response at the ankle joint was also different in the two groups during mid-swing. Conclusions Hemiplegic and healthy middle-aged people presented different phase-modulation of the kinematic and muscle nociceptive reflex responses evoked by stimulation delivered on the sole of the foot. Significance The results have potential application in programs to rehabilitate Hemiplegic Gait.

Ping Zhou - One of the best experts on this subject based on the ideXlab platform.

  • post stroke Hemiplegic Gait new perspective and insights
    Frontiers in Physiology, 2018
    Co-Authors: Sheng Li, Gerard E Francisco, Ping Zhou
    Abstract:

    Walking dysfunction occurs at a very high prevalence in stroke survivors. Human walking is a phenomenon often taken for granted, but it is mediated by complicated neural control mechanisms. The automatic process includes the brainstem descending pathways (RST and VST) and the intraspinal locomotor network. It is known that leg muscles are organized into modules to serve subtasks for body support, posture and locomotion. Major kinematic mechanisms are recognized to minimize the center of gravity (COG) displacement. Stroke leads to damage to motor cortices and their descending corticospinal tracts and subsequent muscle weakness. On the other hand, brainstem descending pathways and the intraspinal motor network are disinhibited and become hyperexcitable. Recent advances suggest that they mediate post-stroke spasticity and diffuse spastic synergistic activation. As a result of such changes, existing modules are simplified and merged, thus leading to poor body support and walking performance. The wide range and hierarchy of post-stroke Hemiplegic Gait impairments is a reflection of mechanical consequences of muscle weakness, spasticity, abnormal synergistic activation and their interactions. Given the role of brainstem descending pathways in body support and locomotion and post-stroke spasticity, a new perspective of understanding post-stroke Hemiplegic Gait is proposed. Its clinical implications for management of Hemiplegic Gait are discussed. Two cases are presented as clinical application examples.