Percussive Perceptions is a personal exploration of how I emotionally connect to the music when I dance. I noticed that my affinity toward a song affected the way I moved (i.e., my body resonated with the music better the more I liked a song). I wondered if I could see a pattern in the way a voice or an instrument from a song reverberated through my body, and see if that connected with how I felt about the song. To explore this, I designed and built an interactive ballroom shoe and used the cha-cha-cha as the style of dance to see how my rhythm synchronized with song elements.
First, to collect information about my timing to the beat, I attached pressure sensors at the heel. The sensors were connected to Adafruit Bluefruit EZ-Key to interface with the computer. Step counts were collected via GarageBand and analyzed through Audacity to collect the timing of the step.
Second, in order to isolate my emotional connection to the music, I chose four different songs with the same beats per minute (BPM) and used the same choreography. From top to bottom, songs are listed in reverse order of musical complexity (e.g., “Lolita” has the highest complexity while “Shape of You” has the lowest complexity).
|Song||My rating*||Description of musical complexity|
|Lolita||★||Vocals, keyboard, brass and percussion|
|Sway||★★★★||Vocals, brass, and percussion|
|Blurred Lines (Instrumental)||★★||Vocals (limited), percussion|
|Shape of You (Cha Cha Remix)||★★★||Keyboard, sound effects, percussion|
The basic pattern of the cha-cha-cha has five beats: 2, 3, cha-cha-1. The beats denoted by a number have a whole count, while the beats denoted by “cha” are a half count. One typically takes a step on a beat. Preliminary data has been collected using finger taps on the keyboard representative of the aforementioned beat pattern to obtain a sense of sample output. Thus, the data below shows instances of how my fingers respond to this basic beat pattern. Data is normalized to the first beat.
This project is still a work in progress, as data collected with the interactive ballroom shoe is not as clean as finger tap data. However, my intent is to (1) improve data collection with the interactive shoe, (2) elucidate differences between ideal data (finger taps) and data collected from the interactive shoe.
Video showing interactive shoe in action and method of data collection through GarageBand. The data collection in the video is from finger tap data and not representative of real shoe data.