This paper presents a comparison of features derived from various biomedical signals from both younger as well as elderly subjects. The dataset consists of accelerometer, gyroscope and altimeter signals acquired from wearable sensors, describing three different activities of daily living: walking, running and sitting on a chair. The features of all three signal data were processed, and later analysed to determine whether significant differences between signals recorded by younger subjects and elder subjects are present. Results of this comparison could prove valuable in the field of signal processing for various applications (activity recognition, fall detection, elderly care etc.) in terms of rehabilitation.