Spinoscope's performance

A Self-Contained 3D Biomechanical Analysis Lab for Complete Automatic Spine and Full Skeleton Assessment of Posture, Gait and Run

Quantitative functional assessment of Posture and Motion Analysis of the entire skeleton and spine is highly desirable. Nonetheless, in most studies focused on posture and movement biomechanics, the spine is only grossly depicted because of its required level of complexity. Approaches integrating pressure measurement devices with stereophotogrammetric systems have been presented in the literature, but spine biomechanics studies have rarely been linked to baropodometry. A new multi-sensor system called GOALS-E.G.G. (Global Opto-electronic Approach for Locomotion and Spine-Expert Gait Guru), integrating a fully genlock-synched baropodometric treadmill with a stereophotogrammetric device, is introduced to overcome the above-described limitations. The GOALS-EGG extends the features of a complete 3D parametric biomechanical skeleton model, developed in an original way for static 3D posture analysis, to kinematic and kinetic analysis of movement, gait and run. By integrating baropodometric data, the model allows the estimation of lower limb net-joint forces, torques and muscle power. Net forces and torques are also assessed at intervertebral levels. All the elaborations are completely automatised up to the mean behaviour extraction for both posture and cyclic-repetitive tasks, allowing the clinician/researcher to perform, per each patient, multiple postural/movement tests and compare them in a unified statistically reliable framework.

The impact of inefficient clinical diagnosis on the cost of managing low back pain

The clinical examination remains the pivotal factor in evaluating low back pain (LBP) for decisions concerning compensation and rehabilitation. Many practitioners believe it to be highly reliable, even though existing literature does not support this belief. Not only are there no data supporting the efficacy of clinical diagnosis for LBP, but also published data underscore its many inherent weaknesses. Healthcare risk managers need accurate clinical information to make decisions. If current clinical information is unreliable, then healthcare risk management strategies for LBP must be revised. This article reviews the work of many researchers in their attempts to unravel the problem of diagnosing LBP. The following conclusions were reached: The problem is significant and continues to increase. The problem is rooted in the clinician's strong dependency on reported pain, which may not always be a reliable source of objective information. Quantification of the impact of the objectivity of reported pain on clinical performance demonstrates the need for a independent source of functional data that can improve the diagnosis. Technology exists to complement the clinical examination, improve clinical performance, and thus reduce the cost associated with LBP management. The research results presented in this article unveil disturbing findings for healthcare risk managers. The strong bias clinicians reserve for reported pain may lead them to overrate pathology, treat patients inappropriately, prescribe unnecessary imaging tests, and generate unfounded medical opinions that are responsible for many disputes. Data are presented to demonstrate the financial benefits that result from the introduction of systematic objective controls via technology. These sound management principles allow the risk manager to determine the validity of claims and treatment proposals. Risk managers can then make informed decisions on contentious claims and regulate the large number of clinician-supported disability cases--decisions that represent significant savings.