During a veterinary practice consult trip I got the chance to play with a canine stance analyzer. This specialized piece of equipment is used to measure weight distribution in the canine. Academically speaking, dogs bear 60% of their weight on their front limbs and 40% on their rear. There is a little learning curve on how to use the equipment, but all in all it was pretty easy to understand and I started collecting data on all the patients we saw for a two day period(about 15 animals). The numbers that I was getting also seemed to correlate with normal subjective gait analysis and the pathologies we were seeing. I decided to take the technology to a different level, as I wanted to see how weight was being distributed during the Ipsilateral Bridging exercise. I have developed many variations of this exercise but for study purposes we picked the simple version and stuck to one angle like at the time mark of 0:22 in this video:
When using this piece of equipment it seemed more accurate to freeze frame at least 10 “good” postures then average the numbers to obtain a more accurate result of the animals weight distribution. I did this with all the patients I saw over the two day period and continued to use this method with studying Pogo at a normal stance as well as in the ipsilateral bridge.
Pogo’s results were that she bears 8% more weight on her rear than the average dog. And during the ipsilateral bridge she distributed 95% of her weight on her down sided limbs. She also would shift more weight to her rear during the bridge, ~1-2% on her front vs ~3-4% on her rear.
Setting up the study was fun and did take a little trial and error. I wanted to make sure we could show, in real time, how weight was being distributed for future review and so that we could put out a short video on what we had learned. I first thought that using a webcam connected to the analysis computer would give us a reference of body posture and position during the study. I thought if I could run a screen capturing program in the background, and use a simple split screen, then I could easily correlate both the video and the analysis in one video. That worked but not as well as I wanted… So I borrowed some of my movie making knowledge and decided that syncing an outside camera to the analysis computer using a simple audible clap would make for easy syncing in post production. This worked much better than the first idea and I was able to sync up both the video from he analysis computer that was being recored by the screen capturing program as well as the DSLR camera showing body position and posture.
Check out the final video here, it was really fun to make. I’d love to get data on all my exercises, and at some point I will hopefully be able to get more equipment like this so I can.