title: What wrist should you wear your actigraphy device on? Analysis of dominant vs. non-dominant wrist actigraphy for measuring sleep in healthy adults

authors: Driller, Matthew W.

subjects: polysomnography

abstract: OBJECTIVE: Differences in sleep results due to the placement of actigraphy devices (non-dominant vs. dominant wrist) are yet to be determined. 
METHODS: 65 nights of data from 13 adult participants was collected while participants wore two actigraphy devices, one on each wrist. Sleep indices including total sleep time (TST), total time in bed (TTB), sleep efficiency (SE%), sleep latency (SL), wake after sleep onset (WASO), sleep onset time (SOT) and wake time (WT) were assessed between the two devices. 
RESULTS: There were no significant differences between devices for any of the measured sleep variables (p>0.05). SE%, SL and WASO resulted in high correlations between devices (0.89, 0.89 and 0.76, respectively), with all other sleep variables resulting in very high correlations (>0.90) between devices.
CONCLUSIONS: Based on our results, it does not seem critical which wrist the actigraphy device is worn on for measuring key sleep variables.

text: What wrist should you wear your actigraphy device on? Analysis of dominant vs. non-dominant wrist actigraphy for measuring sleep in healthy adults OBJECTIVE: Differences in sleep results due to the placement of actigraphy devices (non-dominant vs. dominant wrist) are yet to be determined. 
METHODS: 65 nights of data from 13 adult participants was collected while participants wore two actigraphy devices, one on each wrist. Sleep indices including total sleep time (TST), total time in bed (TTB), sleep efficiency (SE%), sleep latency (SL), wake after sleep onset (WASO), sleep onset time (SOT) and wake time (WT) were assessed between the two devices. 
RESULTS: There were no significant differences between devices for any of the measured sleep variables (p>0.05). SE%, SL and WASO resulted in high correlations between devices (0.89, 0.89 and 0.76, respectively), with all other sleep variables resulting in very high correlations (>0.90) between devices.
CONCLUSIONS: Based on our results, it does not seem critical which wrist the actigraphy device is worn on for measuring key sleep variables.

year: 2017

title: Cause and Amelioration of MRI-Induced Heating Through Medical Implant Lead Wires

authors: McCabe, Steven Owen

abstract: The RF fields present in magnetic resonance imaging (MRI) scanners can induce hazardous heating in patients wearing medical implants. The inherent design and locale of deep brain stimulators (DBS) and spinal cord stimulators (SCS) make them particularly susceptible. We apply antenna concepts and use electromagnetic (EM) simulation to explain the phenomenon and anticipate its sensitivity to lead wire length. We anticipate that a DC resistance of less than 50 Ω/m and an RF impedance of more than 1:23kΩ/m would be required for a safe electrode for SCS use. We investigate the possibility of manipulating wire conductivity and diameter in order to use the skin depth effect to achieve a safe electrode. The effect of the thickness and permittivity of insulation surrounding the wires is explored.

text: Cause and Amelioration of MRI-Induced Heating Through Medical Implant Lead Wires The RF fields present in magnetic resonance imaging (MRI) scanners can induce hazardous heating in patients wearing medical implants. The inherent design and locale of deep brain stimulators (DBS) and spinal cord stimulators (SCS) make them particularly susceptible. We apply antenna concepts and use electromagnetic (EM) simulation to explain the phenomenon and anticipate its sensitivity to lead wire length. We anticipate that a DC resistance of less than 50 Ω/m and an RF impedance of more than 1:23kΩ/m would be required for a safe electrode for SCS use. We investigate the possibility of manipulating wire conductivity and diameter in order to use the skin depth effect to achieve a safe electrode. The effect of the thickness and permittivity of insulation surrounding the wires is explored.

year: 2014

title: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language

authors: Cocks, John

subjects: Māori

abstract: This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

text: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

year: 2012