<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Assessment of spatio-temporal gait parameters using inertial measurement units in neurological populations."
Abstract:"Laboratory based gait analysis techniques are expensive, time consuming and require technical expertise. Inertial measurement units can directly measure temporal parameters and in combination with gait models may provide a solution to obtain spatial gait measurements within daily clinical assessments. However it is not known if a model and standard correction factor determined by Zijlstra and Hof [8] to estimate step and stride length parameters in typically developed adults (TDA) can be accurately used in neurologically impaired gaits. This research estimated the stride length over two 10 m walks at self selected walking speed in people with neurological conditions, using a previously established model and correction factor for TDA. The relation of the correction factor to walking speed was explored. We recruited TDA (n = 10) and participants with Parkinson's disease (PD; n = 24), muscular dystrophy (MD; n = 13), motor neuron disease (MND; n = 7) and stroke survivors (n = 18) for the study who twice walked 10 m at a self-selected pace. Stride length correction factors, for TDA (1.25 +/- 0.01), PD (1.25 +/- 0.03), and MD (1.21 +/- 0.08) (p = 0.833 and p = 0.242) were the same as previously reported in TDA (Zijlstra and Hof [8]). Correction factors for stroke (1.17 +/- 0.42) and MND (1.10 +/- 0.08) were different (p < 0.01 and p = 0.028 respectively). However there was a high level of variability for correction factors within groups, which did not relate to walking speed. Our findings support that correction factors should be determined for each individual to estimate average step/stride length in patients suffering from a neurological condition. (C) 2011 Elsevier B.V. All rights reserved.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

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Assessment of spatio-temporal gait parameters using inertial measurement units in neurological populations
Laboratory based gait analysis techniques are expensive, time consuming and require technical expertise. Inertial measurement units can directly measure temporal parameters and in combination with gait models may provide a solution to obtain spatial gait measurements within daily clinical assessments. However it is not known if a model and standard correction factor determined by Zijlstra and Hof [8] to estimate step and stride length parameters in typically developed adults (TDA) can be accurately used in neurologically impaired gaits. This research estimated the stride length over two 10 m walks at self selected walking speed in people with neurological conditions, using a previously established model and correction factor for TDA. The relation of the correction factor to walking speed was explored. We recruited TDA (n = 10) and participants with Parkinson's disease (PD; n = 24), muscular dystrophy (MD; n = 13), motor neuron disease (MND; n = 7) and stroke survivors (n = 18) for the study who twice walked 10 m at a self-selected pace. Stride length correction factors, for TDA (1.25 +/- 0.01), PD (1.25 +/- 0.03), and MD (1.21 +/- 0.08) (p = 0.833 and p = 0.242) were the same as previously reported in TDA (Zijlstra and Hof [8]). Correction factors for stroke (1.17 +/- 0.42) and MND (1.10 +/- 0.08) were different (p < 0.01 and p = 0.028 respectively). However there was a high level of variability for correction factors within groups, which did not relate to walking speed. Our findings support that correction factors should be determined for each individual to estimate average step/stride length in patients suffering from a neurological condition. (C) 2011 Elsevier B.V. All rights reserved.