## 2 Materials and Methods
### Three-Dimensional Motion Capture and Biomechanical Modeling  
A 12-camera VICON MX40 motion capture system (Oxford Metrics Ltd., Oxford, UK) was set up to capture the movements. Cameras were placed in a circle around the subjects, creating a capture volume of approximately 5 \(\times\) 5 \(\times\) 3 m. The motion capture tracked and triangulated the positions of markers made from 3M Super-reflective Tape that are placed on the subject, i.e., the captured data supplied the spatial position of the markers. The use of motion-capture permits considerable freedom of movement without influencing the accuracy of data, so no restrictions were placed on the movement of the subjects within the capture volume and the subjects could perform the selected movement without having to alter their normal body language. Using the manufacturer's specified guidelines, calibration resolution yielded results accurate to <1 mm. Data was gathered at 250 frames/second, which allows the finest details of movement to be accurately examined.  
Forty-four spherical, reflective markers (diameter = 9 mm) were placed on each participant (Figures 2 and 3). Forty-two were located at the standard anatomic landmarks necessary to create a 15 segment, full-body biomechanical model [19; 20; 21]. The placement of body markers was as follows: four markers on the head (one each on the left and right temples and two on the posterior portion of the parietal bone); six markers on the upper trunk (one each on the sternal notch, xiphoid process, C7 and T10 vertebrae and the left & right back); seven markers on each upper limb (acromion processes, lateral epicondyles of the humerus, styloid processes of the ulna and radius, third metacarpophalangeal joints, and upper and lower arms); four markers on the pelvis (one each on left and right anterior and posterior superior iliac crests); and six markers on each lower limb (upper thigh, lateral condyle of the tibia, lateral side of the tibia, lateral malleolus of the fibula, calcaneal tuberosity, head of halluces) (Figure 4). The additional two markers were placed at the left and right bottom of the back (representing the left and right bottom of a vest) for a possible consideration of sensor positions.  
Figure 3: Motion analysis/quantification of the common daily activities among seniors: (**a**) a walk with eyes-closed (followed by a trip); (**b**) going upstairs; (**c**) walking downstairs; (**d**) sitting down and standing up; (**e**) reaching for an object.  
After positional data was captured, it was applied to a 15-segment biomechanical model. The 15 segments were head, upper torso, lower torso, upper arms, forearms, hands, thighs, legs, and feet. Data was filtered using a five-point moving average filter (weighted: 1-3-4-3-1). The model calculations supplied the positions, speeds, and accelerations of each marker, as well as all joint angles: flexion/extension (Flex/Ext), abduction/adduction (Ab/Add), and rotation, i.e., the motor controls of fall and non-fall situations. A 3D sample of side-fall characterized by the 15-segment biomechanical body model was shown in Figure 5. In 3D body modeling, inertial characteristics for each segment were determined by applying anthropometric regression equations with individual body mass, body height, and gender as input parameters [19]. Using the biomechanical model, sensitive sensor locations and threshold values for distinguishing daily activities and falls were quantified.