Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Prehension, the act of reaching to grasp an object, is used for many daily functions including acquiring food items for eating, grooming, manipulating objects, wielding tools, and communicating through gesture and written word. The most prominent theory concerning the neurobehavioral control of prehension, the Dual Visuomotor Channel theory^1,2,3,4, proposes that prehension consists of two movements – a reach that transports the hand to the location of the target and a grasp that opens, shapes, and closes the hand to the size and shape of the target. The two movements are mediated by dissociable but interacting neural pathways from visual to motor cortex via the parietal lobe^1,2,3,4. Behavioral support for the Dual Visuomotor Channel theory has been ambiguous, largely due to the fact that the reach-to-grasp movement appears as a single seamless act and unfolds with little conscious effort. Nonetheless, prehension is almost always studied in the context of visually-guided prehension in which a healthy participant reaches to grasp a visible target object. Under these circumstances the action does appear as a single movement that unfolds in a predictable and stereotypical fashion. Prior to reach onset the eyes fixate on the target. As the arm extends the digits open, preshape to the size of the object, and subsequently start to close. The eyes disengage from the target just prior to target contact and final grasp of the target follows almost immediately afterwards⁵. When vision is removed, however, the structure of the movement is fundamentally different. The movement dissociates into its constituent components such that an open-handed reach is first used to locate the target by touching it and then haptic cues associated with target contact guide shaping and closure of the hand to grasp⁶.

Quantification of the reach-to-grasp movement is most often achieved using a 3 dimensional (3D) motion tracking system. These can include infrared tracking systems, electromagnetic tracking systems, or video based tracking systems. While such systems are effective for acquiring kinematic measures of prehension in healthy adult participants performing stereotypical reach-to-grasp movements towards visible target objects, they do have a number of drawbacks. In addition to being very expensive, these systems require the attachment of sensors or markers onto the arm, hand, and digits of the participant. These are usually attached using medical tape, which can impede tactile feedback from the hand, alter natural motor behavior, and distract participants⁷. As these systems generally produce numerical output related to different kinematic variables such as acceleration, deceleration, and velocity they are also not ideal for investigating how the hand contacts the target. When using these systems, additional sensors or equipment are required to determine what part of the hand makes contact with the target, where on the target contact occurs, and how the configuration of the hand might change in order to manipulate the target. In addition, infrared tracking systems, which are the most commonly employed, require the use of a specialized camera to track the location of the markers on the hand in 3D space⁶. This requires a direct line of sight between the camera and the sensors on the hand. As such, any idiosyncrasies in the movement are likely to obscure this line of sight and result in the loss of critical kinematic data. There are, however, a large number of instances in which idiosyncrasies in the reach-to-grasp movement are actually the norm. These include during early development when infants are just learning to reach and grasp for objects; when the target object is not visible and tactile cues must be used to guide the reach and the grasp; when the target object is an odd shape or texture; and when the participant presents with any one of a variety of sensorimotor disorders such as a stroke, Huntington's disease, Parkinson's disease, Cerebral Palsy, etc. In all of these cases, the reach-to-grasp movement is neither predictable nor stereotypical, nor is it necessarily guided by vision. Consequently, the capability of 3D motion tracking systems to reliably quantify the temporal and kinematic structure of these movements can be severely limited due to disruptions in sensory feedback from the hand, changes in natural motor behavior, loss of data, and/or difficulties interpreting the idiosyncratic kinematic output from these devices.

The present paper describes a novel technique for quantifying idiosyncratic reach-to-grasp movements in various human populations that is affordable, does not impede sensory feedback from the hand or natural motor behavior, and is reliable but can be flexibly modified to suit a variety of experimental paradigms. The technique involves using multiple high-speed video cameras to record the reach-to-grasp movement from multiple angles. The video is then analyzed offline by progressing through the video frames one at a time and using visual inspection to document key behavioral events that, together, provide a quantified description of the temporal and kinematic organization of the reach-to-grasp movement. The present paper describes a comparative analysis of visually- versus nonvisually-guided reach-to-grasp movements in healthy human adults^6,8,9,10 in order to demonstrate the efficacy of the technique; however, modified versions of the technique have also been used to quantify the reach-to-grasp actions of human infants¹¹ and non-human primates¹². The comprehensive results of the frame-by-frame video analysis from these studies are among the first to provide behavioral evidence in support of the Dual Visuomotor Channel theory of prehension.