Outcome measures used in trials on gait rehabilitation in multiple sclerosis: A systematic literature review

Background Multiple Sclerosis (MS) is associated with impaired gait and a growing number of clinical trials have investigated efficacy of various interventions. Choice of outcome measures is crucial in determining efficiency of interventions. However, it remains unclear whether there is consensus on which outcome measures to use in gait intervention studies in MS. Objective We aimed to identify the commonly selected outcome measures in randomized controlled trials (RCTs) on gait rehabilitation interventions in people with MS. Additional aims were to identify which of the domains of the International Classification of Functioning, Disability and Health (ICF) are the most studied and to characterize how outcome measures are combined and adapted to MS severity. Methods Pubmed, Cochrane Central, Embase and Scopus databases were searched for RCT studies on gait interventions in people living with MS according to PRISMA guidelines. Results In 46 RCTs, we identified 69 different outcome measures. The most used outcome measures were 6-minute walking test and the Timed Up and Go test, used in 37% of the analyzed studies. They were followed by gait spatiotemporal parameters (35%) most often used to inform on gait speed, cadence, and step length. Fatigue was measured in 39% of studies. Participation was assessed in 50% of studies, albeit with a wide variety of scales. Only 39% of studies included measures covering all ICF levels, and Participation measures were rarely combined with gait spatiotemporal parameters (only two studies). Conclusions Selection of outcome measures remains heterogenous in RCTs on gait rehabilitation interventions in MS. However, there is a growing consensus on the need for quantitative gait spatiotemporal parameter measures combined with clinical assessments of gait, balance, and mobility in RCTs on gait interventions in MS. Future RCTs should incorporate measures of fatigue and measures from Participation domain of ICF to provide comprehensive evaluation of trial efficacy across all levels of functioning.

Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor

Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters can be used to determine asymmetric walking. The spatiotemporal parameter has the disadvantage that it does not consider the influence of the diversity of patterns and the walking speed. Therefore, in this paper, we propose a method to analyze asymmetric walking using Dynamic Time Warping (DTW) distance, a time series analysis method. The DTW distance was obtained by combining gyroscope data and pressure data. The experiment was carried out by performing symmetrical walking and asymmetrical walking, and asymmetric walking was performed as a simulation of hemiplegic walking by fixing one ankle using an auxiliary device. The proposed method was compared with the existing asymmetric gait analysis method. As a result of the experiment, a p-value lower than 0.05 was obtained, which proved that there was a statistically significant difference.

Screening of Early Warning Parameters of Dengue Fever Syndrome in Mengla County Based on Space-Time Rearrangement Scanning Statistics

Objective: The objective of this study was to establish the combination of time and space parameters for spatiotemporal rearrangement scanning. The spatial and temporal rearrangement of dengue cluster events was performed by using dengue syndrome to evaluate the effects of different spatiotemporal parameter combinations on the early warning effect. This study aimed to select the best spatiotemporal parameter combination for early warning of dengue syndrome and establish a perfect early warning model of dengue syndrome based on spatiotemporal rearrangement scan statistics.Methods: The data of dengue syndrome in eighty medical institutions (including township hospitals and village clinics) in the symptom monitoring system of medical institutions in Mengla County in 2017 and the data of reported cases of dengue in the direct reporting system of infectious diseases were collected using Excel to describe the time, region and population distribution of dengue fever. The Java server page was scanned to establish different spatiotemporal parameter combinations (X, Y). X was the time parameter, and Y was the space parameter. The maximum number of early warning days was set to four, and when including the date of the gathering event, a total of five days. The dengue fever clusters in Mengla County in 2017 were scanned day by day in time and space, and the sensitivity and the number of days of advance warning were used as the warning indicators to comprehensively evaluate the warning effects of nine warning schemes.Results: 1. A total of two hundred forty-seven cases of dengue fever were reported in Mengla County in 2017, with an incidence rate of 85.79/100,000. The peak incidence was mainly from August to November; cases of dengue fever reported by the infectious disease direct reporting system were distributed over eight medical institutions. Mengla County People's Hospital had the largest number of reported cases; the ratio of males to females was roughly balanced (approximately 1:1). The largest population distribution was 100 cases in farmers (40.49%), followed by 50 cases of business service personnel (20.24%). 2. Nine different spatiotemporal parameter combinations were used to scan a total of 225 times, which were performed for five dengue fever clusters in Mengla County in 2017. The aggregation region, LLR(Log Likelihood Ratio), RR and P values of the warning under each scan combination were obtained. 3. Sensitivity analysis of nine parameter combinations for five dengue aggregation events included the following: the (3, 10), (4, 10), (5, 10), (4, 15), (5, 15) combination alerted to five dengue aggregation events, and the sensitivity was 100%; the (3, 15) combination alerted to four dengue aggregation events, and the sensitivity was 80%; the (3, 5), (4, 5), (5, 5) combination alerted to three dengue aggregation events, and the sensitivity was 60%. 4. Analysis of the early warning times of five dengue aggregation events by nine parameter combinations resulted in the following: the (3, 10) combination early warning times of five dengue aggregation events were three days, four days, four days, one day and one day, with an average early warning time of two point six days; the (4, 10), (5, 10) combination early warning times of five dengue aggregation events were two days, three days, four days, one days and zero day, respectively, with an average early warning time of two days; the (3, 15) combination early warning times of five dengue aggregation events were zero day, four days, four days, one day and one day, with an average early warning time of two days; the (5, 15) combination early warning times of five dengue aggregation events were one day, four days, four days, one day and zero day, with an average early warning time of 2 days; the (4, 5), (5, 5), (4,15) combination early warning times of five dengue aggregation events were zero day, four days, three days, one day and zero day, with an average early warning time of one point six days; the (3, 5) combination early warning times of five dengue aggregation events were one day, four days, three days, zero day and zero day, with an average early warning time of one point six days. 5. Analysis of the duration warning time of five dengue aggregation events by nine parameter combinations included the following: for the (3, 10) combination among the five dengue aggregation events, the average duration warning days was two point two days; for the (4, 10), (5, 10), (5, 15) combination among the five dengue aggregation events; the average duration warning days was two days, and the average duration warning days of other parameter combinations were less than two days.Conclusions: 1. Dengue fever has an obvious seasonal trend in Mengla County, and the cases are mainly concentrated in summer and autumn. In this time period, we should strengthen the corresponding prevention and control of dengue fever, especially the main gathering areas of farmers and commercial service groups. 2. Based on the data of dengue syndrome, time-space rearrangement scanning of dengue clustering events in Mengla County was carried out, and the optimal time-space clustering combination was selected. In the future, the combination of the (3, 10) parameters can be preferentially used for the early warning of dengue outbreaks in this area by using dengue syndrome. In addition, the combination of the (4, 10), (5, 10), and (5, 15) parameters can be used as an alternative parameter combination. 3. In the future, when the optimal parameter combination is used for the early warning of dengue fever, a graded response can be adopted according to the actual situation, which maximally ensures that real aggregation events are detected while avoiding excessive waste of resources.

Vitality form expression in autism

The notion of “vitality form” has been coined by Daniel Stern to describe the basic features of action, which may reflect the mood or affective state of an agent. There is general consensus that vitality forms substantiate social interactions in children as well in adults. Previous studies have explored children with Autism Spectrum Disorder (ASD)’s ability in copying and recognizing the vitality forms of actions performed by others. In this paper we investigated, for the first time, how children with ASD express different vitality forms when acting themselves. We recorded the kinematics of ASD and typically developing (TD) children while performing three different types of action with two different vitality forms. There were two conditions. In the what condition we contrasted the three different types of action performed with a same vitality form, while in the how condition we contrasted the same type of action performed with two different vitality forms. The results showed a clear difference between ASD children and TD children in the how, but not in the what, condition. Indeed, while TD children distinguished the vitality forms to be expressed by mostly varying a specific spatiotemporal parameter (i.e. movement time), no significant variation in this parameter was found in ASD children. As they are not prone to express vitality forms as neurotypical individuals do, individuals with ASD’s interactions with neurotypical peers could therefore be difficult to achieve successfully, with cascading effects on their propensity to be tuned to their surrounding social world, or so we conjecture. If this conjecture would turn out to be correct, our findings could have promising implication for theoretical and clinical research in the context of ASD.