Wearable sensors have been used to collect information on individual exposure to excessive heat and humidity. To date, no consistent diurnal classification method has been established, potentially resulting in missed opportunities to understand personal diurnal patterns in heat exposure. Using individually experienced temperatures (IET) and heat indices (IEHI) collected in the southeastern United States, this work aims to determine whether current methods of classifying IETs and IEHIs accurately characterize "day," which is typically the warmest conditions, and "night," which is typically the coolest conditions. IET and IEHI data from four locations were compared with the closest hourly weather station. Different day/night classifications were compared to determine efficacy. Results indicate that diurnal IET and IEHI ranges are higher than fixed-site ranges. Maximum IETs and IEHIs are warmer and occur later in the day than ambient conditions. Minimum IETs are lower and occur earlier in the day than at weather stations, which conflicts with previous assumptions that minimum temperatures occur at night. When compared to commonly used classification methods, a method of classifying day and night based on sunrise and sunset times best captured the occurrence of maximum IETs and IEHIs. Maximum IETs and IEHIs are often identified later in the evening, while minimum IETs and IEHIs occur throughout the day. These findings support future research focusing on nighttime heat exposure, which can exacerbate heat-related health issues, and diurnal patterns of personal exposure throughout the entire day as individual patterns do not necessarily follow the diurnal pattern seen in ambient conditions.