Publication date: September 2017
Source:Gait & Posture, Volume 57
Author(s): Rafael Caldas, Marion Mundt, Wolfgang Potthast, Fernando Buarque de Lima Neto, Bernd Markert
The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) algorithms to gait analysis based on inertial sensor data, verifying if they can support the clinical evaluation. Articles were identified through searches of the main databases, which were encompassed from 1968 to October 2016. We have identified 22 studies that met the inclusion criteria. The included papers were analyzed due to their data acquisition and processing methods with specific questionnaires. Concerning the data acquisition, the mean score is 6.1±1.62, what implies that 13 of 22 papers failed to report relevant outcomes. The quality assessment of AI algorithms presents an above-average rating (8.2±1.84). Therefore, AI algorithms seem to be able to support gait analysis based on inertial sensor data. Further research, however, is necessary to enhance and standardize the application in patients, since most of the studies used distinct methods to evaluate healthy subjects.
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Τετάρτη 28 Ιουνίου 2017
Cognitive-motor interference in multiple sclerosis: What happens when the gait speed is fixed?
Publication date: September 2017
Source:Gait & Posture, Volume 57
Author(s): Ofir Malcay, Yevgenia Grinberg, Shani Berkowitz, Leora Hershkovitz, Alon Kalron
During the last decade, numerous studies have confirmed a coupling between walking performance and cognition in people with multiple sclerosis (PwMS). Our aim was to provide new insights into a walking-cognitive dual-task (DT) in PwMS. We tested the DT phenomenon by controlling the walking speed using an instrumented treadmill. Thirty PwMS (20 women) with a mean age 40.1 (SD=12.0) participated in the study. Twenty-one healthy subjects served as controls. Each subject completed a sequence of tests: a) Normal walking (ST) − the participant walked on the instrumented treadmill at a comfortable walking speed for 1min; b) Cognitive evaluation (ST) − subjects performed two cognitive tests while seated; c) DT cognitive tests performed while walking on the treadmill at the identical speed performed during normal walking. Outcome measures were spatio-temporal parameters of gait (mean and variability), the Word List Generation Test (WLG) and the Serial-3 Subtraction Test. MS participants significantly decreased their cadence while increasing their stride length during the DT condition compared to the ST condition. Non-significant differences were observed for the WLG and Serial-3 Subtraction Cognitive Tests between the ST condition and the DT condition in both the MS and healthy groups. In terms of gait variability parameters, MS subjects demonstrated a 2 to 3-fold greater gait variability compared to the healthy controls. Non-significant differences in gait variability parameters were observed between the ST and DT conditions in both the MS and control groups. This study provides new insights into the DT phenomenon in the MS population.
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Source:Gait & Posture, Volume 57
Author(s): Ofir Malcay, Yevgenia Grinberg, Shani Berkowitz, Leora Hershkovitz, Alon Kalron
During the last decade, numerous studies have confirmed a coupling between walking performance and cognition in people with multiple sclerosis (PwMS). Our aim was to provide new insights into a walking-cognitive dual-task (DT) in PwMS. We tested the DT phenomenon by controlling the walking speed using an instrumented treadmill. Thirty PwMS (20 women) with a mean age 40.1 (SD=12.0) participated in the study. Twenty-one healthy subjects served as controls. Each subject completed a sequence of tests: a) Normal walking (ST) − the participant walked on the instrumented treadmill at a comfortable walking speed for 1min; b) Cognitive evaluation (ST) − subjects performed two cognitive tests while seated; c) DT cognitive tests performed while walking on the treadmill at the identical speed performed during normal walking. Outcome measures were spatio-temporal parameters of gait (mean and variability), the Word List Generation Test (WLG) and the Serial-3 Subtraction Test. MS participants significantly decreased their cadence while increasing their stride length during the DT condition compared to the ST condition. Non-significant differences were observed for the WLG and Serial-3 Subtraction Cognitive Tests between the ST condition and the DT condition in both the MS and healthy groups. In terms of gait variability parameters, MS subjects demonstrated a 2 to 3-fold greater gait variability compared to the healthy controls. Non-significant differences in gait variability parameters were observed between the ST and DT conditions in both the MS and control groups. This study provides new insights into the DT phenomenon in the MS population.
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Accuracy of step count measured by physical activity monitors: The effect of gait speed and anatomical placement site
Publication date: September 2017
Source:Gait & Posture, Volume 57
Author(s): Jessica J. Chow, Jeanette M. Thom, Michael A. Wewege, Rachel E. Ward, Belinda J. Parmenter
IntroductionConsumer-based physical activity monitors (PAMs) are becoming increasingly popular, with multiple global organisations recommending physical activity levels that equate to 10,000 steps per day for optimal health. We therefore aimed to compare the step count of five PAMs to a visual step count to identify the most accurate monitors at varying gait speeds, along with the optimal anatomical placement site.MethodsParticipants completed 3min on a treadmill for five speeds (5.0km/h, 6.5km/h, 8.0km/h, 10km/h, 12km/h). An Actigraph wGT3XBT-BT was placed on the waist and wrist, a FitBit One on the waist, and a Fitbit Flex, Fitbit Charge HR and Jawbone UP24 on both wrists. A video of participant’s lower limbs was recorded for visual count. Analyses of variance (ANOVAs) were conducted to examine the effects of gait speed and device placement site on step count accuracy.ResultsThirty-one participants (mean age 24.3±5.2yrs) took part. Step count error ranged from 41.3±13.8% for the wrist-worn Actigraph to only 0.04±4.3% and −0.3±4.0% for the waist-worn Fitbit One and Actigraph, respectively. Across all gait speeds, waist-worn devices achieved better accuracy than those on the wrist (p<0.001). The Jawbone was the most accurate wrist-worn consumer-based device at slower speeds (p=0.026), with the Fitbit Flex, and Fitbit Charge HR increasing in accuracy to match the Jawbone at higher speeds.ConclusionThe accuracy and reliability of consumer-based PAMs and the Actigraph is affected by anatomical placement site and walking speed. The Fitbit One and Actigraph on the waist were the strongest performers across all speeds.
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Source:Gait & Posture, Volume 57
Author(s): Jessica J. Chow, Jeanette M. Thom, Michael A. Wewege, Rachel E. Ward, Belinda J. Parmenter
IntroductionConsumer-based physical activity monitors (PAMs) are becoming increasingly popular, with multiple global organisations recommending physical activity levels that equate to 10,000 steps per day for optimal health. We therefore aimed to compare the step count of five PAMs to a visual step count to identify the most accurate monitors at varying gait speeds, along with the optimal anatomical placement site.MethodsParticipants completed 3min on a treadmill for five speeds (5.0km/h, 6.5km/h, 8.0km/h, 10km/h, 12km/h). An Actigraph wGT3XBT-BT was placed on the waist and wrist, a FitBit One on the waist, and a Fitbit Flex, Fitbit Charge HR and Jawbone UP24 on both wrists. A video of participant’s lower limbs was recorded for visual count. Analyses of variance (ANOVAs) were conducted to examine the effects of gait speed and device placement site on step count accuracy.ResultsThirty-one participants (mean age 24.3±5.2yrs) took part. Step count error ranged from 41.3±13.8% for the wrist-worn Actigraph to only 0.04±4.3% and −0.3±4.0% for the waist-worn Fitbit One and Actigraph, respectively. Across all gait speeds, waist-worn devices achieved better accuracy than those on the wrist (p<0.001). The Jawbone was the most accurate wrist-worn consumer-based device at slower speeds (p=0.026), with the Fitbit Flex, and Fitbit Charge HR increasing in accuracy to match the Jawbone at higher speeds.ConclusionThe accuracy and reliability of consumer-based PAMs and the Actigraph is affected by anatomical placement site and walking speed. The Fitbit One and Actigraph on the waist were the strongest performers across all speeds.
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Gait parameter and event estimation using smartphones
Publication date: September 2017
Source:Gait & Posture, Volume 57
Author(s): Lucia Pepa, Federica Verdini, Luca Spalazzi
Background and objectivesThe use of smartphones can greatly help for gait parameters estimation during daily living, but its accuracy needs a deeper evaluation against a gold standard. The objective of the paper is a step-by-step assessment of smartphone performance in heel strike, step count, step period, and step length estimation. The influence of smartphone placement and orientation on estimation performance is evaluated as well.MethodsThis work relies on a smartphone app developed to acquire, process, and store inertial sensor data and rotation matrices about device position. Smartphone alignment was evaluated by expressing the acceleration vector in three reference frames. Two smartphone placements were tested. Three methods for heel strike detection were considered. On the basis of estimated heel strikes, step count is performed, step period is obtained, and the inverted pendulum model is applied for step length estimation. Pearson correlation coefficient, absolute and relative errors, ANOVA, and Bland–Altman limits of agreement were used to compare smartphone estimation with stereophotogrammetry on eleven healthy subjects.ResultsHigh correlations were found between smartphone and stereophotogrammetric measures: up to 0.93 for step count, to 0.99 for heel strike, 0.96 for step period, and 0.92 for step length. Error ranges are comparable to those in the literature. Smartphone placement did not affect the performance. The major influence of acceleration reference frames and heel strike detection method was found in step count.ConclusionThis study provides detailed information about expected accuracy when smartphone is used as a gait monitoring tool. The obtained results encourage real life applications.
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Source:Gait & Posture, Volume 57
Author(s): Lucia Pepa, Federica Verdini, Luca Spalazzi
Background and objectivesThe use of smartphones can greatly help for gait parameters estimation during daily living, but its accuracy needs a deeper evaluation against a gold standard. The objective of the paper is a step-by-step assessment of smartphone performance in heel strike, step count, step period, and step length estimation. The influence of smartphone placement and orientation on estimation performance is evaluated as well.MethodsThis work relies on a smartphone app developed to acquire, process, and store inertial sensor data and rotation matrices about device position. Smartphone alignment was evaluated by expressing the acceleration vector in three reference frames. Two smartphone placements were tested. Three methods for heel strike detection were considered. On the basis of estimated heel strikes, step count is performed, step period is obtained, and the inverted pendulum model is applied for step length estimation. Pearson correlation coefficient, absolute and relative errors, ANOVA, and Bland–Altman limits of agreement were used to compare smartphone estimation with stereophotogrammetry on eleven healthy subjects.ResultsHigh correlations were found between smartphone and stereophotogrammetric measures: up to 0.93 for step count, to 0.99 for heel strike, 0.96 for step period, and 0.92 for step length. Error ranges are comparable to those in the literature. Smartphone placement did not affect the performance. The major influence of acceleration reference frames and heel strike detection method was found in step count.ConclusionThis study provides detailed information about expected accuracy when smartphone is used as a gait monitoring tool. The obtained results encourage real life applications.
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Porównanie częstości występowania objawów współistniejących w grupie pacjentów z zawrotami głowy.
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Related Articles |
Porównanie częstości występowania objawów współistniejących w grupie pacjentów z zawrotami głowy.
Otolaryngol Pol. 2017 Feb 28;71(1):34-39
Authors: Šichnárek J, Vyskotová J, Macháčková K, Mrázková E
Abstract
BACKGROUND: Dizziness is the second most frequent symptom that make patients seek specialized examination. The effective solution of dizzy conditions requires treatment in cooperation with different branches of medicine.
OBJECTIVE: To analyze data from the database of patients with vertigo examined in the Hearing and Balance Disorder Centre in Ostrava, to find out whether, and in what factors, the sets of patients with diagnosed central and peripheral vestibular syndrom differ from each other.
METHODS: Retrospective study that was carried out from October 2012 to February 2013. The data was gathered from documentation of all vertiginous patients who were examined by an otoneurologist.
RESULTS: The statistically significant difference between the two sets was found in: occurrence of hypertension and mild obesity, impaired hearing and otitis media, stabilometric testing CONCLUSIONS: There was a statistically significant difference between the sets with the central and peripheral vestibular syndrome in the frequency of occurrence of hypertension, impaired hearing, otitis media, in mild obesity categorization and in balance disorders. There was not any statistically significant difference found in the other observed factors. The results confirm the need of a multidisciplinary approach to patients with vertigo.
PMID: 28485291 [PubMed - indexed for MEDLINE]
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Quantitative Pneumatic Otoscopy Using a Light-Based Ranging Technique
Abstract
Otitis media is the leading cause of hearing loss in children. It is commonly associated with fluid in the ear, which can result in up to 45 dB of hearing loss for extended periods of time during a child’s most important developmental years. Accurate assessment of middle ear effusions is an important part of understanding otitis media. Current technologies used to diagnose otitis media with effusion are pneumatic otoscopy, tympanometry, and acoustic reflectometry. While all of these techniques can reasonably diagnose the presence of an effusion, they provide limited information about the infection present behind the tympanic membrane.
We have developed a technique based on low-coherence interferometry—a non-invasive optical ranging technique capable of sensing depth-resolved microscopic scattering features through the eardrum—to quantify eardrum thickness and integrity, as well as detect any effusion, purulence, or biofilm behind the tympanic membrane. In this manuscript, the technique is coupled with a pneumatic otoscope to measure minute deflections of the tympanic membrane from insufflation pressure stimuli. This results in quantitative measurements of tympanic membrane mobility, which may be used to gain a better understanding of the impact of infection on the membrane dynamics. A small pilot study of 15 subjects demonstrates the ability of pneumatic low-coherence interferometry to quantitatively differentiate normal ears from ears with effusions present. Analysis of the strengths and weaknesses of the technique, as well as focus areas of future research, is also discussed.
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Τρίτη 27 Ιουνίου 2017
Re: Gaskill CS, Awan JA, Watts CR, Awan SN. Acoustic and perceptual classification of within-sample normal, intermittently dysphonic, and consistently dysphonic voice types. J Voice. 2016;31:218–228
Source:Journal of Voice
Author(s): Philipp Aichinger, Gernot Kubin
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