E-textiles, particularly knitted resistive strain sensors, have been proposed for joint motion measurements. Although combining non-elastic conductive yarns with elastic non-conductive yarns improves sensor performance, the effects of knitting patterns and strategies for integrating sensors into garments remain underexplored. This paper addresses both by: (1) comparing the characteristics of plain weft-knitted resistive strain sensors made from conductive silver-coated yarn and Lycra-based elastic yarn across multiple patterns, and (2) evaluating three integration methods–hand-sewn attachment to finished garments, snap-button attachment, and direct in-garment knitting. We find that the plated knitting pattern with conductive material on the knit side and the elastic non-conductive yarn on the purl side achieves the best sensor characteristics, with a gauge factor of 14.616 during stretching and 13.300 during release. For joint angle estimation, we compare multi-layer perceptrons and a random forest under both static holds and continuous motion for all three integration methods. Performance degradation from resistance drift can be substantially mitigated through pre-processing, including linear detrending and predicting relative rather than absolute angles. However, models trained on one integration method show limited transferability to others, underscoring the need for method-specific calibration. This work provides practical guidance on the design, fabrication, integration and data processing of knitted strain sensors for joint motion measurement.