The ultimate goal of a computer system is to satisfy its users. The success of architectural or system-level optimizations depends largely on having accurate metrics for user satisfaction. We propose to derive such metrics from information that is "close to flesh" and apparent to the user rather than from information that is "close to metal" and hidden from the user. We describe and evaluate PICSEL, a dynamic voltage and frequency scaling (DVFS) technique that uses measurements of variations in the rate of change of a computer's video output to estimate user-perceived performance. Our adaptive algorithms, one conservative and one aggressive, use these estimates to dramatically reduce operating frequencies and voltages for graphically-intensive applications while maintaining performance at a satisfactory level for the user. We evaluate PICSEL through user studies conducted on a Pentium M laptop running Windows XP. Experiments performed with 20 users executing three applications indicate that the measured laptop power can be reduced by up to 12.1%, averaged across all of our users and applications, compared to the default Windows XP DVFS policy. User studies revealed that the difference in overall user satisfaction between the more aggressive version of PICSEL and Windows DVFS were statistically insignificant, whereas the conservative version of PICSEL actually improved user satisfaction when compared to Windows DVFS.