The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Carlos Singer - One of the best experts on this subject based on the ideXlab platform.
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tandem Gait Abnormality in parkinson disease prevalence and implication as a predictor of fall risk
Parkinsonism & Related Disorders, 2019Co-Authors: Jason Margolesky, Sagari Bette, Tatjana Rundek, Corneliu C Luca, Henry Moore, Danielle S Shpiner, Elizabeth Jordan, Chuanhui Dong, Carlos SingerAbstract:Abstract Introduction We report the prevalence of abnormal tandem Gait (TG) in patients with idiopathic Parkinson disease (PD) and its association with symptoms of subjective unsteadiness, falls, freezing of Gait, and cognitive impairment. Methods We assessed subjective balance impairment, fall history, antero-posterior postural instability, and TG in PD patients (Hoehn and Yahr (HY) stage 0–4). We recorded the age, sex, current medications, HY stage, Schwab and England (S&E) scale score, and MOCA score for each patient. Logistic regression was used to evaluate age-adjusted associations between TG and other demographic and clinical factors. Results A total of 102 patients with PD were assessed. Of those, 63.5% of HY 2 patients and 100% of HY 2.5 and 3 patients had a TG Abnormality. The presence of TG Abnormality was associated with subjective imbalance, falls, freezing of Gait, S&E Conclusions TG Abnormality is common in PD, precedes the development of antero-posterior postural instability, is associated with cognitive impairment, and may predict fall risk. A longitudinal study will help determine if TG is a predictor of impending progression from HY 2 to HY 3.
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the prevalence of tandem Gait Abnormality in parkinson s disease p2 075
Neurology, 2018Co-Authors: Jason Margolesky, Sagari Bette, Danielle Spengler, Tatjana Rundek, Corneliu C Luca, Henry Moore, Carlos SingerAbstract:Objective: to assess the prevalence of tandem Gait (TG) Abnormality in patients with Parkinson’s disease (PD), comparing Hoen and Yahr (HY) stages II and III. Background: Classically, as Parkinson’s disease (PD) progresses, patients develop antero-posterior instability detected by the pull test. Detecting this Abnormality defines the transition from HY stages II and III. Historically, detecting a mediolateral balance impairment, via TG testing, in a patient with parkinsonism was considered a “red flag” for an atypical parkinsonism. Design/Methods: Our study protocol assessed subjective balance impairment, fall history, antero-posterior postural instability, and quantified TG Abnormality in PD patients. To test TG, patients were asked to walk heel-to-toe for 10 consecutive steps with their arms at their sides and eyes open. The number of missteps in 10 were counted. Patients were allowed two trials, and the best performance was scored—as defined by the relevant sections of the UHDRS and SARA scales. Postural instability was defined by the pull test (MDS-UPDRS 3.12). We recorded the age, sex, current medications, HY stage, Schwab and England Scale and MOCA score for each patient. Patients with clinically apparent peripheral sensory neuropathy, gross orthopedic Abnormality or concern for atypical PD were excluded. Results: 50 patients with PD were assessed, 23 woman and 27 men, from ages 52 to 81 years. 31 patients were HY 2; 5 patients HY 2.5; and 3 patients HY 3. 58% of HY 2 patients had a TG Abnormality. 100% of HY stages 2.5 and 3 patients had a TG Abnormality. Conclusions: TG Abnormality is common in Parkinson’s disease patients and it preceded the development of anteroposterior balance instability in our cohort. Detecting a TG Abnormality in a patient with PD may predict fall risk. A follow up longitudinal study will help determine if TG is a predictor of impending progression from HY2 to HY3. Disclosure: Dr. Margolesky has nothing to disclose. Dr. Bette has nothing to disclose. Dr. Shpiner has nothing to disclose. Dr. Rundek has nothing to disclose. Dr. Luca has nothing to disclose. Dr. Moore has nothing to disclose. Dr. Singer has nothing to disclose.
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Gait Abnormality in essential tremor
Movement Disorders, 2004Co-Authors: Carlos Singer, Juan Sanchezramos, William J WeinerAbstract:Essential tremor (ET) has been described as a monosymptomatic disorder. In reports describing large series of patients with ET, there are rare patients who exhibit a noticeable Gait disorder. However, we have observed that patients with ET and normal Gait often exhibit an Abnormality of tandem Gait. To investigate this observation, we examined whether a Gait disorder was present in 36 consecutive patients (mean age 69) with ET. We employed a tremor rating scale that scored tremor amplitude, location, and disability. In all patients, Gait and tandem Gait were separately evaluated. Eighteen of 36 patients (50%) exhibited tandem Gait abnormalities in the presence of a normal narrow-based Gait compared to 11 of 40 age-matched controls (28%) (p 5 years of disease duration. No relationship was found between presence of tandem Gait Abnormality and gender, tremor severity, head involvement, or positive family history. The finding of a tandem Gait Abnormality in 50% of ET patients suggests that cerebellar dysfunction may be important in its pathophysiology.
Sarah L. Whitehouse - One of the best experts on this subject based on the ideXlab platform.
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measurement of Gait Abnormality one year after tha using a portable six sensor imu system
Orthopaedic Proceedings, 2018Co-Authors: Aj Timperley, F Doyle, Sarah L. WhitehouseAbstract:IntroductionImprovements in function after THA can be evaluated using validated health outcome surveys but studies have shown that PROMs are unreliable in following the progress of individuals. Formal Gait lab analysis is expensive, time consuming and fixed in terms of location. Inertial Measurement Units (IMUs) containing accelerometers and gyroscopes can determine aspects of Gait kinematics in a portable package and can be used in the outpatient setting (Figure 1). In this study multiple metrics describing Gait were evaluated pre- and post THA and comparisons made with the normal populationMethodsThe Gait of 55 patients with monarthrodial hip arthrosis was measured pre-operatively and at one year post-surgery. Patients with medical co-morbidity or other condition affecting their Gait were excluded. Six IMUs aligned in the sagittal plane were attached at the level of the anterior superior iliac spines, mid-thigh and mid-shank. Data was analysed using proprietary software (Figure 2). Each patient underwen...
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MEASUREMENT OF Gait Abnormality ONE YEAR AFTER THA USING A PORTABLE SIX SENSOR IMU SYSTEM
Journal of Bone and Joint Surgery-british Volume, 2017Co-Authors: Aj Timperley, F Doyle, Sarah L. WhitehouseAbstract:Introduction Improvements in function after THA can be evaluated using validated health outcome surveys but studies have shown that PROMs are unreliable in following the progress of individuals. Formal Gait lab analysis is expensive, time consuming and fixed in terms of location. Inertial Measurement Units (IMUs) containing accelerometers and gyroscopes can determine aspects of Gait kinematics in a portable package and can be used in the outpatient setting (Figure 1). In this study multiple metrics describing Gait were evaluated pre- and post THA and comparisons made with the normal population Methods The Gait of 55 patients with monarthrodial hip arthrosis was measured pre-operatively and at one year post-surgery. Patients with medical co-morbidity or other condition affecting their Gait were excluded. Six IMUs aligned in the sagittal plane were attached at the level of the anterior superior iliac spines, mid-thigh and mid-shank. Data was analysed using proprietary software (Figure 2). Each patient underwent a conventional THA using a posterolateral approach. An identical test was performed one year after surgery. 92 healthy individuals with a normal observed Gait were used as controls. Results In the pre-operative test the range of movement in the sagittal plane of both the ipsilateral hip (mean range 20.4) and the contra-lateral non-diseased hip (35.3 degrees) was reduced compared to the control group (40.5 degrees), (P After one year the range of movement of the ipsilateral hip significantly improved (Mean range 28.9 deg SD 6.6) but did not attain normal values (P Discussion and Conclusion Gait after routine THA does not return to normal on the ipsilateral or contralateral side. Pathology in one hip causes bilateral Gait Abnormality that can be quantified by movement at the pelvis, hip, thigh and knee. The ability of a patient to walk normally after surgery will depend on many factors including details of the hip operation such as accurate recreation of the biomechanics of the joint and physical therapy regimens. Advances in technology now allow assessment of Gait in large number of patients in the clinic setting and will better allow us to establish the important factors to improve patients Gait and thereby potentially improve further satisfaction and PROMS scores. For any figures or tables, please contact authors directly (see Info & Metrics tab above).
Anup Nandy - One of the best experts on this subject based on the ideXlab platform.
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human Gait Abnormality detection using low cost sensor technology
International Conference on Computer Vision, 2020Co-Authors: Shaili Jain, Anup NandyAbstract:Detection of Gait Abnormality is becoming a growing concern in different neurological and musculoskeletal patients group including geriatric population. This paper addresses a method of detecting abnormal Gait pattern using deep learning algorithms on depth Images. A low cost Microsoft Kinect v2 sensor is used for capturing the depth images of different subject’s Gait sequences. A histogram-based technique is applied on depth images to identify the range of depth values for the subject. This method generates segmented depth images and subsequently median filter is used on them to reduce unwanted information. Multiple 2D convolutional neural network (CNN) models are trained on segmented images for pathological Gait detection. But these CNN models are only restricted to spatial features. Therefore, we consider 3D-CNN model to include both spatial and temporal features by stacking all the images from a single Gait cycle. A statistical technique based on autocorrelation is applied on entire Gait sequences for finding the Gait period. We achieve a significant detection accuracy of 95% using 3D-CNN model. Performance evaluation of the proposed model is evaluated through standard statistical metrics.
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discrete wavelet transform based data representation in deep neural network for Gait Abnormality detection
Biomedical Signal Processing and Control, 2020Co-Authors: Jayeeta Chakraborty, Anup NandyAbstract:Abstract Detection of abnormal Gait patterns using wearable sensors remains a major challenge in clinical Gait analysis and rehabilitation field. Despite the success of recent researches using deep learning techniques, the prospects of improvement in the classification process with the help of modification in data representation is largely overlooked. In this paper, a deep neural network-based framework is proposed where discrete wavelet decomposition is used for data representation to detect abnormal Gait patterns using inertial sensors. In the proposed approach, the walking Gait data of healthy children and cerebral palsy children are collected using two inertial sensors. Discrete wavelet transform is applied to signal segments to form decomposed signal segments. A multi-channel 1-dimensional convolutional neural network (1D-CNN) model is trained with the decomposed signals. The proposed method achieves 96.4% and 90.97% accuracy for segment-wise and subject-wise evaluation respectively. The performance of the proposed model is compared with the state-of-the-art methods as well as with a basic 1D-CNN model trained with signals directly. Analysis of the result shows that the proposed method performs significantly better than the basic CNN model and also exceeds over the performance of the state-of-the-art methods. An investigation is done on the effect on the performance of the model with varying levels of wavelet decomposition which reveals that at level 2, the proposed method reaches the highest accuracy and lowest loss value. When tested with 100 random samples, the wavelet representation generates higher area-under-curve scores for deep learning based techniques, compared to empirical mode decomposition representation method.
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Gait Abnormality detection in people with cerebral palsy using an uncertainty based state space model
International Conference on Computational Science, 2020Co-Authors: Saikat Chakraborty, Noble Thomas, Anup NandyAbstract:Assessment and quantification of feature uncertainty in modeling Gait pattern is crucial in clinical decision making. Automatic diagnostic systems for Cerebral Palsy Gait often ignored the uncertainty factor while recognizing the Gait pattern. In addition, they also suffer from limited clinical interpretability. This study establishes a low-cost data acquisition set up and proposes a state-space model where the temporal evolution of Gait pattern was recognized by analyzing the feature uncertainty using Dempster-Shafer theory of evidence. An attempt was also made to quantify the degree of Abnormality by proposing Gait deviation indexes. Results indicate that our proposed model outperformed state-of-the-art with an overall \(87.5\%\) of detection accuracy (sensitivity \(80.00\%\), and specificity \(100\%\)). In a Gait cycle of a Cerebral Palsy patient, first double limb support and left single limb support were observed to be affected mainly. Incorporation of feature uncertainty in quantifying the degree of Abnormality is demonstrated to be promising. Larger value of feature uncertainty was observed for the patients having higher degree of Abnormality. Sub-phase wise assessment of Gait pattern improves the interpretability of the results which is crucial in clinical decision making.
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human Gait modelling using hidden markov model for Abnormality detection
IEEE Region 10 Conference, 2018Co-Authors: Sourav Chattopadhyay, Anup NandyAbstract:This paper presents a novel approach to human Gait analysis using wearable Inertial Measurement Unit(IMU) sensor-based technique. The proposed system emphasizes on detection of certain abnormal Gait patterns. It includes hemiplegic and equinus Gait which are synthetically generated in our lab. The designed prototype contains an IMU sensor with 3 axial accelerometer and gyroscope. It provides linear acceleration and angular velocity of human foot. A probabilistic framework, Hidden Markov Model(HMM) is applied to model bipedal human Gait. This model uses Symbolic Aggregate Approximation(SAX) method for generating observation sequences obtained from sample Gait cycles.The detection of abnormal Gait pattern is based on maximum log-likelihood of an unknown observerd sequence, generated from a Gait cycle. The experimental results demonstarte that the proposed HMM-based technique is able to detect Gait Abnormality in Gait data. The proposed personalized Gait modelling approach is cost effective and reliable to implement in Gait rehabilatation process.
Aj Timperley - One of the best experts on this subject based on the ideXlab platform.
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measurement of Gait Abnormality one year after tha using a portable six sensor imu system
Orthopaedic Proceedings, 2018Co-Authors: Aj Timperley, F Doyle, Sarah L. WhitehouseAbstract:IntroductionImprovements in function after THA can be evaluated using validated health outcome surveys but studies have shown that PROMs are unreliable in following the progress of individuals. Formal Gait lab analysis is expensive, time consuming and fixed in terms of location. Inertial Measurement Units (IMUs) containing accelerometers and gyroscopes can determine aspects of Gait kinematics in a portable package and can be used in the outpatient setting (Figure 1). In this study multiple metrics describing Gait were evaluated pre- and post THA and comparisons made with the normal populationMethodsThe Gait of 55 patients with monarthrodial hip arthrosis was measured pre-operatively and at one year post-surgery. Patients with medical co-morbidity or other condition affecting their Gait were excluded. Six IMUs aligned in the sagittal plane were attached at the level of the anterior superior iliac spines, mid-thigh and mid-shank. Data was analysed using proprietary software (Figure 2). Each patient underwen...
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MEASUREMENT OF Gait Abnormality ONE YEAR AFTER THA USING A PORTABLE SIX SENSOR IMU SYSTEM
Journal of Bone and Joint Surgery-british Volume, 2017Co-Authors: Aj Timperley, F Doyle, Sarah L. WhitehouseAbstract:Introduction Improvements in function after THA can be evaluated using validated health outcome surveys but studies have shown that PROMs are unreliable in following the progress of individuals. Formal Gait lab analysis is expensive, time consuming and fixed in terms of location. Inertial Measurement Units (IMUs) containing accelerometers and gyroscopes can determine aspects of Gait kinematics in a portable package and can be used in the outpatient setting (Figure 1). In this study multiple metrics describing Gait were evaluated pre- and post THA and comparisons made with the normal population Methods The Gait of 55 patients with monarthrodial hip arthrosis was measured pre-operatively and at one year post-surgery. Patients with medical co-morbidity or other condition affecting their Gait were excluded. Six IMUs aligned in the sagittal plane were attached at the level of the anterior superior iliac spines, mid-thigh and mid-shank. Data was analysed using proprietary software (Figure 2). Each patient underwent a conventional THA using a posterolateral approach. An identical test was performed one year after surgery. 92 healthy individuals with a normal observed Gait were used as controls. Results In the pre-operative test the range of movement in the sagittal plane of both the ipsilateral hip (mean range 20.4) and the contra-lateral non-diseased hip (35.3 degrees) was reduced compared to the control group (40.5 degrees), (P After one year the range of movement of the ipsilateral hip significantly improved (Mean range 28.9 deg SD 6.6) but did not attain normal values (P Discussion and Conclusion Gait after routine THA does not return to normal on the ipsilateral or contralateral side. Pathology in one hip causes bilateral Gait Abnormality that can be quantified by movement at the pelvis, hip, thigh and knee. The ability of a patient to walk normally after surgery will depend on many factors including details of the hip operation such as accurate recreation of the biomechanics of the joint and physical therapy regimens. Advances in technology now allow assessment of Gait in large number of patients in the clinic setting and will better allow us to establish the important factors to improve patients Gait and thereby potentially improve further satisfaction and PROMS scores. For any figures or tables, please contact authors directly (see Info & Metrics tab above).
Jason Margolesky - One of the best experts on this subject based on the ideXlab platform.
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tandem Gait Abnormality in parkinson disease prevalence and implication as a predictor of fall risk
Parkinsonism & Related Disorders, 2019Co-Authors: Jason Margolesky, Sagari Bette, Tatjana Rundek, Corneliu C Luca, Henry Moore, Danielle S Shpiner, Elizabeth Jordan, Chuanhui Dong, Carlos SingerAbstract:Abstract Introduction We report the prevalence of abnormal tandem Gait (TG) in patients with idiopathic Parkinson disease (PD) and its association with symptoms of subjective unsteadiness, falls, freezing of Gait, and cognitive impairment. Methods We assessed subjective balance impairment, fall history, antero-posterior postural instability, and TG in PD patients (Hoehn and Yahr (HY) stage 0–4). We recorded the age, sex, current medications, HY stage, Schwab and England (S&E) scale score, and MOCA score for each patient. Logistic regression was used to evaluate age-adjusted associations between TG and other demographic and clinical factors. Results A total of 102 patients with PD were assessed. Of those, 63.5% of HY 2 patients and 100% of HY 2.5 and 3 patients had a TG Abnormality. The presence of TG Abnormality was associated with subjective imbalance, falls, freezing of Gait, S&E Conclusions TG Abnormality is common in PD, precedes the development of antero-posterior postural instability, is associated with cognitive impairment, and may predict fall risk. A longitudinal study will help determine if TG is a predictor of impending progression from HY 2 to HY 3.
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the prevalence of tandem Gait Abnormality in parkinson s disease p2 075
Neurology, 2018Co-Authors: Jason Margolesky, Sagari Bette, Danielle Spengler, Tatjana Rundek, Corneliu C Luca, Henry Moore, Carlos SingerAbstract:Objective: to assess the prevalence of tandem Gait (TG) Abnormality in patients with Parkinson’s disease (PD), comparing Hoen and Yahr (HY) stages II and III. Background: Classically, as Parkinson’s disease (PD) progresses, patients develop antero-posterior instability detected by the pull test. Detecting this Abnormality defines the transition from HY stages II and III. Historically, detecting a mediolateral balance impairment, via TG testing, in a patient with parkinsonism was considered a “red flag” for an atypical parkinsonism. Design/Methods: Our study protocol assessed subjective balance impairment, fall history, antero-posterior postural instability, and quantified TG Abnormality in PD patients. To test TG, patients were asked to walk heel-to-toe for 10 consecutive steps with their arms at their sides and eyes open. The number of missteps in 10 were counted. Patients were allowed two trials, and the best performance was scored—as defined by the relevant sections of the UHDRS and SARA scales. Postural instability was defined by the pull test (MDS-UPDRS 3.12). We recorded the age, sex, current medications, HY stage, Schwab and England Scale and MOCA score for each patient. Patients with clinically apparent peripheral sensory neuropathy, gross orthopedic Abnormality or concern for atypical PD were excluded. Results: 50 patients with PD were assessed, 23 woman and 27 men, from ages 52 to 81 years. 31 patients were HY 2; 5 patients HY 2.5; and 3 patients HY 3. 58% of HY 2 patients had a TG Abnormality. 100% of HY stages 2.5 and 3 patients had a TG Abnormality. Conclusions: TG Abnormality is common in Parkinson’s disease patients and it preceded the development of anteroposterior balance instability in our cohort. Detecting a TG Abnormality in a patient with PD may predict fall risk. A follow up longitudinal study will help determine if TG is a predictor of impending progression from HY2 to HY3. Disclosure: Dr. Margolesky has nothing to disclose. Dr. Bette has nothing to disclose. Dr. Shpiner has nothing to disclose. Dr. Rundek has nothing to disclose. Dr. Luca has nothing to disclose. Dr. Moore has nothing to disclose. Dr. Singer has nothing to disclose.
