Two algorithms for evaluating postural transitions (PTs) in cohorts of 40 healthy younger and 40 older adults are described and evaluated. The time of sit-to-stand (SiSt) and stand-to-sit (StSi) transitions and their duration were measured with two tri-axial accelerometers, one on the chest and one on the lower back. Each algorithm was optimized for these sensor placements. The first algorithm for sensor placement on the chest used a scalar product and vertical velocity estimates. The second algorithm for sensor placement on the lower back used a vector magnitude and a discrete wavelet transform. Both algorithms performed excellently in PT classification for younger and older adults (>86%). However, the chest based sensor and algorithm were better for estimating transition duration (TD) with ICCs to video analysis ranging from 0.678 to 0.969.