Research has demonstrated that temperature and relative humidity substantially influence overall perceptions of indoor air quality (Fang, Clausen, & Fanger, 1998). This finding places temperature quality as a high priority, especially for vulnerable adults over 60. Temperature extremes and fluctuation, as well as the perception of those conditions, affect physical performance, thermal comfort and health of older adults (Chatonnet & Cabanac, 1965, pp. 185-6; Fumiharu, Watanabe, Park, Shephard, & Aoyagi, 2005; Heijs & Stringer, 1988). The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) and the International Organization for Standardization (ISO) have developed thermal-comfort standards for working-age, healthy individuals. None of these standards address the physiological and psychological needs of older adults (ASHRAE Standard 55, 2010; ISO-7730, 2005). This dissertation investigates the impacts of thermal conditions on self-reported health and perceived comfort for older adults, hypothesizing that warmer and more-table indoor thermal conditions will increase the health and perceived comfort of these adults. To this end, a new set of thermal comfort metrics was designed and tested to address the thermal preferences of older adults. The SENIOR COMFORT Metrics 2013 outlined new thresholds for optimal indoor high and low temperatures and set limits on thermal variability over time based on the ASHRAE-55 2010 model. This study was conducted at Sunnyslope Manor, a multi-unit, public-housing complex in the North Phoenix. Nearly 60% (76 of 118) of the residents (aged 62-82) were interviewed using a 110-question, self-reporting survey in 73 apartment units. A total of 40 questions and 20 sub-questions addressing perceptions of comfort, pain, sleep patterns, injuries, and mood were extracted from this larger health condition survey to assess health and thermal comfort. Indoor environmental thermal measurements included temperature in three locations: kitchen, living area, and bedroom and data were recorded every 15 minutes over 5 full days and 448 points. Study results start to indicate that older adults for Sunnyslope Manor preferred temperatures between 76 and 82.5 degrees Fahrenheit and that lower temperatures as outlined by ASHRAE-55 2010 increases the rate of injuries and mood changes in older adults among other findings.

Statistical process control (SPC) and predictive analytics have been used in industrial manufacturing and design, but up until now have not been applied to threshold data of vital sign monitoring in remote care settings. In this study of 20 elders with COPD and/or CHF, extended months of peak flow monitoring (FEV1) using telemedicine are examined to determine when an earlier or later clinical intervention may have been advised. This study demonstrated that SPC may bring less than a 2.0% increase in clinician workload while providing more robust statistically-derived thresholds than clinician-derived thresholds. Using a random K-fold model, FEV1 output was predictably validated to .80 Generalized R-square, demonstrating the adequate learning of a threshold classifier. Disease severity also impacted the model. Forecasting future FEV1 data points is possible with a complex ARIMA (45, 0, 49), but variation and sources of error require tight control. Validation was above average and encouraging for clinician acceptance. These statistical algorithms provide for the patient's own data to drive reduction in variability and, potentially increase clinician efficiency, improve patient outcome, and cost burden to the health care ecosystem.