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For older adults, physical functioning status describes how well a person is able to manage necessary daily activities independently. Different tools exist for testing and follow-up of physical functioning state at different levels of health and age. However, technologies have not been widely adapted for monitoring the physical functioning status during daily life in a longitudinal setup. In this thesis, the actigraph's characteristics for evaluating the physical functioning of older adults at various levels of health and functioning are studied. An actigraph measures activity level estimates continuously and is typically worn on the wrist for extended periods. The actigraph is a mature technology that has been used in the sleep research since 1970s. In addition to sleep patterns, the actigraph can assess a subject's physical activity levels, and sleep-wake rhythms. Furthermore, a novel processing concept for evaluating long-term activity pattern responses to external stimuli, such as facility's common activities or weather has been developed in this thesis. This thesis utilizes three different datasets in which actigraph data have been collected online, parallel with physical functioning estimates. The first dataset includes subjects from a nursing home with intermediate to demanding care need, the second dataset subjects are assisted living residents who are mostly independent but might receive some support services, and the third dataset subjects are from a demanding nursing home unit. The third dataset includes longitudinal data (over three years at longest). In addition, a fourth dataset was used to compare the actigraph processing methods between a traditional actigraph and the online actigraph to understand how well the encountered results with datasets 1-3 could be generalized. In the thesis, the actigraph estimates for sleep, activity level and diurnal rhythms are compared with physical functioning results by utilizing datasets 1-3. In combined data from datasets 1 and 2 (demented subjects were excluded from the analysis) higher physical functioning estimate (activities of daily living assessment) was associated with higher physical activity level and with more night-time activity variance. In addition, subjects with better functioning tend to have more similar activity rhythms with the facility activities (novel concept) and less-stable day-to-day activity patterns. In Dataset 3 (now including subjects with and without dementia) better physical functioning was associated with more stable and stronger diurnal activity rhythm. However, the correlation between the diurnal rhythm stability and physical functioning might be explained by the severity of dementia according to the results. In the longitudinal case analysis, most of the activity rhythm patterns were associated with physical functioning changes as expected according to cross sectional analysis. In Dataset 2, the amount of time the subjects spent outside the facility correlated positively with better physical functioning. This suggests that different context information can provide meaningful information on the older adults' health in addition to traditional actigraph estimates. Since the correlations slightly differed depending on the study population we suggest that monitoring activity level, activity rhythm strength, similarity and variability simultaneously is recommended. Sleep patterns were not connected with physical functioning in the utilized datasets. The thesis results suggest that the actigraph is a feasible health monitoring concept to be utilized in assisted living and nursing home settings and is suitable for follow up of changes in activity patterns associated with changes in physical functioning.