Thesis (M. S.)--Psychology, Georgia Institute of Technology, 2009. / Committee Chair: Dr. Gregory M. Corso; Committee Member: Dr. Arthur D. Fisk; Committee Member: Dr. Bruce Walker; Committee Member: Dr. Lawrence R. James; Committee Member: Dr. Paul Corballis; Committee Member: Dr. Robert Gregor

This thesis examines the use of motion detection and analysis systems to detect falls and repetitive motion patterns of at-risk individuals. Three classes of motion are examined: Activities of daily living (ADL), falls, and repetitive motion. This research exposes a simple relationship between ADL and non-ADL movement, and shows how to use Principal Component Analysis and a kNN classifier to tell the 2 classes of motion apart with 100% sensitivity and specificity. It also identifies a more complex relationship between falls and repetitive motion, which both produce bodily accelerations exceeding 3G but differ with regard to their periodicity. This simplifies the classification problem of falls versus repetitive motion when taking into account that their data representations are similar except that repetitive motion displays a high degree of periodicity as compared to falls. / by Clyde Carryl. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Hitting a Major League fastball pitch may be the most difficult task in the sports realm. Anecdotal evidence suggests that certain individuals are able to perform this task reasonably well, perhaps because of superior sensitivity to changes in motion. However, the substantial lack of research investigating detection and assessment of changes in motion renders this conclusion problematic (Kelling, 2008). Two experiments, using expert and novice participants, assessed sensitivity to changes in motion. Experts for these studies were defined as current members of the Georgia Institute of Technology Yellow Jacket softball team. Experimental procedures included assessments of capabilities in batting and motion tracking tasks. Experiment One presented participants with recorded softball pitches thrown from a pitching machine. Experiment Two required participants to predict multiple landing locations for incomplete motion paths resulting from a single main target exploding into additional shrapnel pieces. Results suggest minimal expertise effects in the softball task with high performance by all participants, while distinct expertise effects exist in the shrapnel task. The motion tracking task resulted in fewer errors by experts, while all participants demonstrated a significantly large drop in performance with increasing number of shrapnel pieces. Findings from this work not only have application to the sport of softball, but are critical for identifying the people's capability to detect and assess changes in motion.