Soft strain sensors have been widely used for the development of electronic skins both for robotic and wearable applications. To sense contact location on a wide surface, the standard methodology consists of square grids of strain fibers that are able to detect single contact points but fail to detect multiple ones simultaneously. To avoid such a problem, state-of-the-art technologies implement sequential sampling that isolates each sensing node, but at the cost of a lower sampling rate. This theoretical study proposes a design methodology for multi-touch detection for parallel processed grid-based strain sensors. The fundamental idea is to add diagonal grids of varying orientations on top of the standard architecture to achieve multi-touch detection. The maximum number of detectable points and the number of required strain fibers and the overall geometry of the sensor are studied along with the error introduced when trying to sense more contact points than designed for. Overall, compared with state-of-the-art design methodologies, our work provides a guideline for more efficient grid-based architectures that are able to simultaneously detect up to a fixed finite number of contact points.