Functional kinematics of the wrist

Rainbow, Michael J.; Wolff, Aviva L.; Crisco, Joseph J.; Wolfe, Scott W.

doi:10.1177/1753193415616939

Cited by 78 publications

(54 citation statements)

References 80 publications

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“…Upper body kinematic measures are widely used in ergonomics 1–2 , orthopedics 3–4 , and rehabilitation 5–7 to describe normal and pathological motion of the trunk, head, and arms. Traditional methods of motion capture utilize marker-based and electromagnetic laboratory-based systems to acquire highly accurate (within 1–3°) kinematic quantification 6 .…”

Section: Introductionmentioning

confidence: 99%

Validation of Inertial Measurement Units for Upper Body Kinematics

Morrow¹,

Lowndes²,

Fortune³

et al. 2017

Journal of Applied Biomechanics

103

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The purpose of this study was to validate a commercially available IMU system against a standard lab-based motion capture system for the measurement of shoulder elevation, elbow flexion, trunk flexion/extension and neck flexion/extension kinematics. The validation analyses were applied to six surgical faculty members performing a standard, simulated surgical training task that mimics minimally invasive surgery. Three-dimensional joint kinematics were simultaneously recorded by an optical motion capture system and an IMU system with six sensors placed on the head, chest, and bilateral upper and lower arms. The sensor-to-segment axes alignment was accomplished manually. The IMU neck and trunk IMU flexion/extension angles were accurate to within 2.9±0.9 degrees and 1.6±1.1 degrees, respectively. The IMU shoulder elevation measure was accurate to within 6.8±2.7 degrees and the elbow flexion measure was accurate to within 8.2±2.8 degrees. In the Bland-Altman analyses, there were no significant systematic errors present; however, there was a significant inversely proportional error across all joints. As the gold standard measurement increased, the IMU underestimated the magnitude of the joint angle. This study reports acceptable accuracy of a commercially available IMU system; however, results should be interpreted as protocol specific.

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Section: Introductionmentioning

confidence: 99%

Validation of Inertial Measurement Units for Upper Body Kinematics

Morrow¹,

Lowndes²,

Fortune³

et al. 2017

Journal of Applied Biomechanics

103

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show abstract

“…Our model demonstrates that the bones of the distal and proximal rows move minimally during two distinct wrist motion paths (one along the anatomical axes of wrist motion, and the other oblique to the main axis), but it does not explicitly prove or disprove any particular theory of carpal bone motion that has been developed to date . The row theory described the kinematics of the wrist with two rows organized proximally (lunate and triquetrum) and distally (hamate, capitate, trapezoid, and trapezium), having the scaphoid as a bridge or connection between these two rows.…”

Section: Discussionmentioning

confidence: 82%

“…To describe the carpal bone motion patterns, two major kinematic theories of row and column have been proposed . Although the row theory (describing the distinct motion patterns for proximal and distal carpal rows), column theory (assuming three medial‐central‐lateral carpal columns as an inner mechanism for the wrist motion), and their combinations have helped in devising and evaluating clinical procedures, they are not predictive or specific about individual carpal bone kinematics within the overall wrist motion.…”

mentioning

confidence: 99%

“…Thus far, a predictive model for the carpal bones has not been developed, perhaps in part because of the lack of a detailed kinematic database. Previous attempts at constructing a predictive and informative model of carpal bone motion have been primarily based on radiographic or cadaveric observations . Due to the variations in motion patterns of the carpal bone articulations among wrists and lack of large sample sizes, none of these models have been rigorously evaluated for predictive ability.…”

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confidence: 99%

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Predicting Carpal Bone Kinematics Using an Expanded Digital Database of Wrist Carpal Bone Anatomy and Kinematics

Akhbari

Moore

Laidlaw

et al. 2019

Journal Orthopaedic Research

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The wrist can be considered a 2 degrees-of-freedom joint with all movements reflecting the combination of flexion-extension and radial-ulnar deviation. Wrist motions are accomplished by the kinematic reduction of the 42 degrees-of-freedom of the individual carpal bones. While previous studies have demonstrated the minimal motion of the scaphoid and lunate as the wrist moves along the dart-thrower's path or small relative motion between hamate-capitate-trapezoid, an understanding of the kinematics of the complete carpus across all wrist motions remains lacking. To address this, we assembled an open-source database of in vivo carpal motions and developed mathematical models of the carpal kinematics as a function of wrist motion. Quadratic surfaces were trained for each of the 42carpal bone degrees-of-freedom and the goodness of fits were evaluated. Using the models, paths of wrist motion that generated minimal carpal rotations or translations were determined. Model predictions were best for flexion-extension, radial-ulnar deviation, and volar-dorsal translations for all carpal bones with R 2 > 0.8, while the estimates were least effective for supination-pronation with R 2 < 0.6. The wrist path of motion's analysis indicated that the distal row of carpal bones moves rigidly together (<3°motion), along the anatomical axis of wrist motion, while the bones in the proximal row undergo minimal motion when the wrist moves in a path oblique to the main axes. The open-source dataset along with its graphical user interface and mathematical models should facilitate clinical visualization and enable new studies of carpal kinematics and function.

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“…To date, these advances have been applied to investigate motion of the knee 16; 23; 24 and temporomandibular joint 25; 26 but not to carpal motion. For understanding, diagnosing and selecting appropriate treatment for dynamic instability of the carpus, there is increasing interest for dynamic imaging by hand surgeons and other clinicians [27][28][29] . There has also been a concern that fast gradient-echo based pulse sequences that worked well for other joints may not be technically feasible in the moving wrist because magnetic field inhomogeneities generated by the significant displacement of the tissues during motion may generate substantial artifacts 11 .…”

Section: Introductionmentioning

confidence: 99%

Real-time three-dimensional MRI for the assessment of dynamic carpal instability

Shaw

Foster

Borgese

et al. 2018

Preprint

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Carpal instability is defined as a condition where wrist motion or loading creates mechanical dysfunction, resulting in weakness, pain and decreased function. Often the diagnosis is made late when malalignment is visualized on static radiography, CT, or MRI. When conventional imaging methods do not identify the instability patterns, yet clinical signs associated with instability exist, the diagnosis of dynamic instability is often suggested to describe carpal derangement manifested only during the wrist’s active motion or stress. We addressed the question: can advanced MRI techniques provide quantitative measures for evaluating dynamic carpal instability and supplement standard static MRI acquisition? Our objectives were to [1] develop a real-time, three-dimensional MRI method to image the carpal joints during their active, uninterrupted motion; and [2] demonstrate feasibility of the method for assessing metrics relevant to dynamic carpal instability, thus overcoming limitations of conventional MRI. Twenty wrists (bilateral wrists of ten healthy participants) were scanned during radial-ulnar deviation and clenched-fist maneuvers. Images resulting from two real-time MRI pulse sequences, four sparse data acquisition schemes, and three constrained image reconstruction priors were compared. Image quality was assessed via blinded scoring by two radiologists and quantitative imaging metrics. Data acquisition employing sparse radial sampling with a gradient-recalled-echo acquisition and constrained iterative reconstruction (temporal resolution up to 135 ms per slice) appeared to provide a reasonable tradeoff between imaging speed and quality. This real-time MRI method effectively reduced streaking artifacts arising from data undersampling and enabled the derivation of quantitative measures pertinent to evaluating dynamic carpal instability.

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Functional kinematics of the wrist

Cited by 78 publications

References 80 publications

Validation of Inertial Measurement Units for Upper Body Kinematics

Validation of Inertial Measurement Units for Upper Body Kinematics

Predicting Carpal Bone Kinematics Using an Expanded Digital Database of Wrist Carpal Bone Anatomy and Kinematics

Real-time three-dimensional MRI for the assessment of dynamic carpal instability

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