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Patients in palliative care suffer from a life-threatening disease. Holistic treatment includes control of symptoms (e. g., pain, nausea, sleeplessness) as well as psychosocial and spiritual help which is also extended to the relatives of a patient. For advanced cancer patients in palliative care, a crucial phase is the transition from palliative care in the hospital to the home setting, where care around the clock is not guaranteed any more, leads to an increased number of unplanned hospital re-admissions and emergency visits. Physicians aim to fill this care gap by monitoring physical and social activities as well as vital signs. Daily monitoring data, provided to caregivers, could enable caregivers to timely intervene when symptoms of a patient deteriorate. Besides patients in palliative care, also cancer survivors suffering from cancer-related fatigue could benefit from activity monitoring. Up to now, the remedies and effective treatments for cancer-related fatigue are limited. Research still has to unveil the underlying mechanisms that lead to a state of chronic exhaustedness. Measures that help healthy people like regenerative sleep show no or little effect in fatigued patients. Besides psycho-stimulants that come with the risk of addiction, cognitive behavioural therapy and moderate physical exercise have been shown to be effective. However, research still has to investigate timing, frequency and intensity of physical activity and researchers need a better understanding how the fatigue evolves during the day and in long-term. This thesis investigates the possibilities and limitations of activity monitoring using wearable devices such as smartphones and an armworn devices that is capable of measuring vital signs such as heart rate. Three studies involving cancer patients are conducted: - An interview study including 12 cancer patients enabled a patient-centric design for an Android activity monitoring app for smartphones. - Only using the smartphone as monitoring device, a study with 7 cancer survivors suffering from cancer-related fatigue was conducted as a pre-study in order to gain first experiences and to explore the possible knowledge gain about cancer-related fatigue through activity monitoring. - During a planned study period of 12 weeks per patient, 30 patients in ambulatory palliative care were wearing a smartphone and the arm-worn sensor as monitoring devices. The age range of the study participants was 39 to 85 years. In weekly interviews, patients were asked about their experiences with the devices and their quality of life. The aim of the study was to evaluate feasibility and acceptance of activity monitoring in this patient group. Furthermore, exploratory data analysis investigated the possibilities and limitations of unsupervised methods on this real-world data set. The two data sets, collected during the fatigue study and during the palliative care study, were pre-processed including cleaning steps, classification and clustering methods to add higher level information such as visited locations (anonymized). From these prepared data sets, features were extracted such as number of places visited per day. On the resulting datasets of features, statistical methods were applied to explore relations between sensor data, self-reports and, in case of the palliative care study, emergency visits to the hospital. For the latter analysis, patients who experienced an emergency room visit and those who did not were compared by means of hypothesis testing. For each feature, the underlying alternative hypothesis was that the change of a feature between the first week of study participation at home and the week before an emergency visit (or the last week of study participation for the patients without an emergency visit), differs in the two patient groups. The rate of change was defined by the ratio of the medians of the two weeks. Changes of three features, namely resting heart rate, resting heart rate variability and step speed were identified to have significant group differences: - The resting heart rate had an increasing trend in the group with emergency visits (median=1.01, interquartile range [0.96, 1.12]) and a decreasing trend in the group without an emergency visit (median=0.9, interquartile range [0.89, 0.99]) with a nominal significance of p=.021 and a medium effect size r=.46. - The resting heart rate variability had a decreasing trend in the group with emergency visits (mean=0.81, standard deviation=0.14) and an increasing trend in the group without an emergency visit (mean=1.17, standard deviation=0.46) with a nominal significance of p=.011 and a large effect size r=.53. - The step speed had an increasing trend in the group with emergency visits (median=1.1, interquartile range [1.08, 1.13]) and a decreasing trend in the group without an emergency visit (median=0.99, interquartile range [0.96, 1.04]) with a nominal significance of p=.003 and a large effect size r=.61. In contrast, hypothesis testing for features based on patients’ subjective self-reports for pain, distres and global quality of life did not reveil any significant differences. Hence, activity monitoring of vital signs and physical activity outperformed patients’ self-reports. However, a power analysis based on the three nominally significant results would recommend an independent study with 84 patients to confirm the results of this study. Furthermore, a set of recommendations for future research was concluded from the experiences gained through conducting these studies.