Modern advances in technology have allowed for an increase in the precision with which we are able to measure, record, and affect behavior. These developments suggest that the domains in which behavior analysis might contribute are considerably broader than previously appreciated, for instance the area of behavioral medicine. One way the field of behavior analysis can begin to address problems in behavioral medicine is with biosensor technology, like surface electromyography (sEMG). For sEMG technology to be useful in behavioral medicine, specifically recovery from total knee arthroplasty, a reference value (the maximum voluntary individual contraction-MVIC) must be established. The MVIC value allows for the comparison of data across days and may allow the programming of contingencies. However, current MVIC methods fall short. Study 1 compares MVIC values produced by a participant given the typical instruction only method with two alternative methods: instruction + feedback, and instruction + feedback in a game context. Across 10 participants both feedback conditions lead to higher MVIC values then the instruction only condition. Study 2 applies the MVIC techniques developed during Study 1 to an exercise procedure. Using an MVIC value as the criteria for feedback Study 2 compares the same three conditions, however this time assessing for the conditions under which exercise performance is optimal. Across all 9 participants the instruction + feedback in a game context lead to the participant ‘working harder' and 8 out of 9 participants exceeded the MVIC value more often during this condition then in the other two conditions.