Most falls in older people occur during daily activities. To work on fall prevention, we need to find those people who have impaired balance control and have a high risk of falling. One way to identify people at risk is by challenging their balance control, for example by provoking them with balance perturbations. To be able to prevent a fall, one must quickly and adequately respond to balance perturbations, such as trips and slips. Balance recovery requires fast and powerful reactions. Especially in older adults, these reactions might be affected by physiological limitations such as muscle strength decline. Our experimental studies on tripping over an obstacle showed that the support limb plays an important role in balance recovery by generating the appropriate joint moments during push-off, necessary to restrain the forward angular momentum. Older adults showed similar onsets of muscle activity and joint moments as young adults. However, they had insufficient reduction of the angular rotation during push-off and poorer placement of the recovery limb. This was due to lower rates of moment generation in all support limb joints and a lower peak ankle moment. These results underline that a decline in rate of force generation in older people, due to age-related changes in muscle, tendon and neural properties, can impede fall avoidance and recovery strategies.Besides measuring ones physical capacities, we might also screen peoples balance control and fall risk based on their daily physical activities. Ambulatory measurements of trunk accelerations can provide valuable information on the quality and amount of daily life activities and contribute to the identification of individuals at risk of falls. We investigated the predictive value for prospective falls over a follow-up period of 6 months of parameters on the amount and quality of daily life gait in 169 older adults. We found that the predictive ability of commonly used questionnaires (area under the receiver operating curve (AUC) of 0.68) improved significantly by accelerometry-derived parameters of gait quality (local dynamic stability, intensity, smoothness), quantity (number of strides) and their interactions (AUC of 0.81). Daily-life accelerometry therefore contributes substantially to the identification of individuals at risk of falls and can predict falls with good accuracy.