## 2 Materials and Methods
### Protocol 1: Determination of Distance Limit of Target Detection
Sequential video clips were captured of the metronome with affixed markers, with the arm actively swinging at foot intervals as the smart phone was progressively moved back from the metronome in increments of 1 ft to 20 ft (Figure 5c) as in Protocol 1. The Apple iPhone 8 or newer version video capture rate utilized was 60 fps. Figure 3: Actual images of experimental design set up of single target resolution. A full unidirectional pendulum swing from one endpoint to another endpoint, i.e., left to right, was termed one lap. A total of 10 laps were used to assess mobile target resolution. Figure 4: Protocol 2: Configuration for distance limit of target pair detection and inter-target discrimination. Neon pink or green markers were cut in either, 2 mm, 5 mm, or 10 mm sizes (**a**). Markers were affixed to flat wood stick in either 2 mm, 5 mm, or 10 mm distances apart (**b**). As in Protocol 1, videos were captured at 1 ft increments (**c**). Figure 5: Protocol 3: Configuration for working distance. Neon pink and green markers were cut in 10 \(\times\) 10 mm size (**a**). Neon pink marker was affixed to metronome at distal end of metronome arm, and neon green marker was affixed to the base of the arm (**b**). Metronome was set at 96 bpm, and videos were captured at 1 ft increments up to 20 ft (**c**). The swing angle of a lap was measured along with the radius (the difference from one endpoint to another endpoint in a horizontal direction) and both measurements were used to determine the physical circumference of the pendulum as per Formula (1)  
\[\text{Physical circumference}=\left(2\pi r*\frac{90}{360}\right) \tag{1}\]  
Tracking circumference (the sum of displacements between each tracking point) was then calculated. Physical circumference and tracking circumference were used to calculate statistical error using Formula (2) as a measure of accuracy as follows:  
\[\text{Accuracy}=|\frac{tracking\ circumference-physical\ circumference}{tracking\ circumference+physical\ circumference}| \tag{2}\]  
The lower the error reported, the higher the accuracy of the MO\({}^{2}\)CA system at that distance. Protocol 4: Determination of Effect of Illumination Intensity on Distance Limit of Target Detection and Resolution  
To determine the effect of illumination intensity on marker detection and resolution, Protocol 1 was conducted exactly as detailed above, though under defined ambient light intensities in a home. Light intensity of the testing room was varied by opening/closing window blinds and turning on/off the halogen lights available in the room and measuring the average luminosity of the room using the Lux Light Meter Pro App (Figure 6a). These steps were completed to create a \"bright room\", all lights on and blinds open, i.e., ~300 lux; a \"natural light room\", only blinds open, i.e., ~200 lux; and a \"dark room\", lights off and blinds closed, i.e., ~100 lux (Figure 6b). All experiments were performed in triplicate. Video images captured at each distance increment were processed and the results plotted (Figure 6c). The end points \"distance limit of target detection\" and \"resolution\" were defined as in Protocol 1. Figure 6: Protocol 4: Configuration for testing luminosity. Neon markers were made as in Protocol 1, Lux Light Meter Pro application downloaded and set on an iPhone (**a**). Various luminosities were set by using the Lux Light Meter Pro to average the light in the room (**b**). Videos were captured at 1–20 ft increments with varying luminosities (**c**). Protocol 5: Application of Smart Phone-Based Motion Detection to Clinical Diagnostic Testing Maneuvers  
To determine the applicability of smart phone-based motion detection in clinical assessment, two clinical maneuvers were evaluated, one for localized, regional body element motion, fingers/digits, and one for whole body motion, and whole-body bend/flexibility.