title: Automation of the landing error scoring system using inertial measurement units

authors: Hamilton, Zane

abstract: The quantification of biomechanics is important for making informed decisions when implementing appropriate training interventions for improving performance and reducing injury risk. This study evaluated the viability of movement data provided by wearable inertial measurement units (IMUs) to automate the scoring of the Landing Error Scoring System (LESS). The LESS is an assessment tool used for identifying high-risk movement patterns in a double leg jump landing; however, the LESS is scored by experts using 2D video recordings, which limits large-scale screening. Movement data provided by three IMUs were used to train several out-of-the-box machine learning models, aiming to predict the result of the 17 LESS scoring items individually. Raw movement data was processed and segmented into the key phases of the movement, where additional features were derived from these segments. A supervised learning approach was taken, using a dataset containing 218 LESS scores derived from 40 participants as the desired output for each model. Comparisons were made between various subsets of features, and the features with the greatest importance on accuracy in the best performing models were extracted. Results showed limited improvements to a ZeroR approach, and features with the greatest importance on the best performing models had minimal relevance to the movement involved. Performance of LESS scoring automation using IMU data may be improved with further developments on this approach.

text: Automation of the landing error scoring system using inertial measurement units The quantification of biomechanics is important for making informed decisions when implementing appropriate training interventions for improving performance and reducing injury risk. This study evaluated the viability of movement data provided by wearable inertial measurement units (IMUs) to automate the scoring of the Landing Error Scoring System (LESS). The LESS is an assessment tool used for identifying high-risk movement patterns in a double leg jump landing; however, the LESS is scored by experts using 2D video recordings, which limits large-scale screening. Movement data provided by three IMUs were used to train several out-of-the-box machine learning models, aiming to predict the result of the 17 LESS scoring items individually. Raw movement data was processed and segmented into the key phases of the movement, where additional features were derived from these segments. A supervised learning approach was taken, using a dataset containing 218 LESS scores derived from 40 participants as the desired output for each model. Comparisons were made between various subsets of features, and the features with the greatest importance on accuracy in the best performing models were extracted. Results showed limited improvements to a ZeroR approach, and features with the greatest importance on the best performing models had minimal relevance to the movement involved. Performance of LESS scoring automation using IMU data may be improved with further developments on this approach.

year: 2024-07-28

title: The impact of immigration on child health: Experimental evidence from a migration lottery program

authors: Stillman, Steven

subjects: New Zealand

abstract: This paper uses a unique survey designed by the authors to compare migrant children who enter New Zealand through a random ballot with children in the home country of Tonga whose families were unsuccessful participants in the same ballots. We find that migration increases height and reduces stunting of infants and toddlers, but also increases BMI and obesity among 3- to 5-yr-olds. These impacts are quite large even though the average migrant household has been in New Zealand for less than 1 yr. Additional results suggest that these impacts occur because of dietary change rather than direct income effects. (JEL J61, I12, F22)

text: The impact of immigration on child health: Experimental evidence from a migration lottery program This paper uses a unique survey designed by the authors to compare migrant children who enter New Zealand through a random ballot with children in the home country of Tonga whose families were unsuccessful participants in the same ballots. We find that migration increases height and reduces stunting of infants and toddlers, but also increases BMI and obesity among 3- to 5-yr-olds. These impacts are quite large even though the average migrant household has been in New Zealand for less than 1 yr. Additional results suggest that these impacts occur because of dietary change rather than direct income effects. (JEL J61, I12, F22)

year: 2010

title: Boat electrofishing survey of fish populations in the Ohau Channel in December 2010

authors: Hicks, Brendan J.

abstract: The original purpose of this series of surveys was to apply an independent method to estimate the densities of common smelt and bullies in the Ohau Channel at fixed points along the bank which coincided with trap netting sites used by the National Institute of Water and Atmospheric Research (NIWA). Since the low number of smelt captured by a single day’s boat electrofishing became apparent compared to the numbers captured by seasonal trapping, the aim of the survey has been modified to provide on-going monitoring of the fish communities and abundance in the Ohau Channel, especially fish species that are taonga to Maori (eels, goldfish, and koura).

text: Boat electrofishing survey of fish populations in the Ohau Channel in December 2010 The original purpose of this series of surveys was to apply an independent method to estimate the densities of common smelt and bullies in the Ohau Channel at fixed points along the bank which coincided with trap netting sites used by the National Institute of Water and Atmospheric Research (NIWA). Since the low number of smelt captured by a single day’s boat electrofishing became apparent compared to the numbers captured by seasonal trapping, the aim of the survey has been modified to provide on-going monitoring of the fish communities and abundance in the Ohau Channel, especially fish species that are taonga to Maori (eels, goldfish, and koura).

year: 2011-11-15