Can shoulder joint reaction forces be estimated by neural networks?

To facilitate the development of future shoulder endoprostheses, a long term load profile of the shoulder joint is desired. A musculoskeletal model using 3D kinematics and external forces as input can estimate the mechanical load on the glenohumeral joint, in terms of joint reaction forces. For long term ambulatory measurements, these 3D kinematics can be measured by means of Inertial Magnetic Measurement Systems. Recording of external forces under daily conditions is not feasible; estimations of joint loading should preferably be independent of this input. EMG signals reflect the musculoskeletal response and can easily be measured under daily conditions. This study presents the use of a neural network for the prediction of glenohumeral joint reaction forces based upon arm kinematics and shoulder muscle EMG. Several setups were examined for NN training, with varying combinations of type of input, type of motion, and handled weights. When joint reaction forces are predicted by a trained NN, for motion data independent of the training data, results show a high intraclass correlation (ICC up to 0.98) and relative SEM as low as 3%, compared to similar output of a musculoskeletal model. A convenient setup in which kinematics and only one channel of EMG were used as input for the NN׳s showed comparable predictive power as more complex setups. These results are promising and enable long term estimation of shoulder joint reaction forces outside the motion lab, independent of external forces.

Determining a long term ambulatory load profile of the shoulder joint: neural networks predicting input for a musculoskeletal model.

To gain more insight in the development of joint damage, a long term load profile of the shoulder joint under daily living conditions is desirable. Standard musculoskeletal models estimate joint load using kinematics and exerted force. However, the latter cannot be measured continuously in ambulatory settings, hampering the use of these models. This paper describes a method for obtaining such a load profile, by training a Neural Network (NN), using kinematics and EMG. A small data set of specified movements with known exerted forces is used in two ways. First, the model calculates several variables of joint load, and a set of Generalized Forces and Net Moments (GFNM) around the model's degrees of freedom. Second, using kinematics and EMG, an NN is trained to predict these GFNM, which can concurrently be used as input for the model, resulting in full model output independent of exerted force. The method is validated with an independent trial. The NN could predict GFNM within 10% relative RMS, compared to output of the model. The NN-model combination estimated joint reaction forces with relative RMS values of 7 to 17%, enabling the estimation of a detailed load profile of the shoulder under daily conditions.

Magnetic distortion in motion labs, implications for validating inertial magnetic sensors.

BACKGROUND: Ambulatory 3D orientation estimation with Inertial Magnetic Sensor Units (IMU's) use the earth magnetic field. The magnitude of distortion in orientation in a standard equipped motion lab and its effect on the accuracy of the orientation estimation with IMU's is addressed. METHODS: Orientations of the earth magnetic field vectors were expressed in the laboratory's reference frame. The effect of a distorted earth magnetic field on orientation estimation with IMU's (using both a quaternion and a Kalman fusing algorithm) was compared to orientations derived from an optical system. FINDINGS: The magnetic field varied considerably, with the strongest effects at 5 cm above floor level with a standard deviation in heading of 29 degrees , decreasing to 3 degrees at levels higher than 100 cm. Orientation estimation was poor with the quaternion filter, for the Kalman filter results were acceptable, despite a systematic deterioration over time (after 20-30s). INTERPRETATION: Distortion of the earth magnetic field is depending on construction materials used in the building, and should be taken into account for calibration, alignment to a reference system, and further measurements. Mapping the measurement volume to determine its ferromagnetic characteristics in advance of planned experiments can be the rescue of the data set. CONCLUSIONS: To obtain valid data, "mapping" of the laboratory is essential, although less critical with the Kalman filter and at larger distances (>100 cm) from suspect materials. Measurements should start in a "safe" area and continue no longer than 20-30s in a heavily distorted earth magnetic field.

Ambulatory measurement of arm orientation.

In order to evaluate the impact of neuromuscular disorders affecting the upper extremities, the functional use of the arm need to be evaluated during daily activities. A system suitable for measuring arm kinematics should be ambulatory and not interfere with activities of daily living. A measurement system based on miniature accelerometers and gyroscopes is adequate because the sensors are small and do not suffer from line of sight problems. A disadvantage of such sensors is the cumulative drift around the vertical and the problems with aligning the sensor with the segment. A method that uses constraints in the elbow to measure the orientation of the lower arm with respect to the upper arm is described. This requires a calibration method to determine the exact orientation of each of the sensors with respect to the segment. Some preliminary measurements were analyzed and they indicated a strong reduction in orientation error around the vertical. It seemed that the accuracy of the method is limited by the accuracy of the sensor to segment calibration.

The effect of an ergonomic computer device on muscle activity of the upper trapezius muscle during typing.

OBJECTIVE: Investigate whether an ergonomic computer device, characterised by an inclined working area and keyboard localisation close to the screen (the Up-Line), decreases the muscle activity of the upper trapezius muscle. METHODS: In a crossover design 19 healthy subjects and 19 patients with Whiplash Associated Disorder (WAD) typed during 10 min at the Up-Line and at a standard workstation with 15 min of rest in between. During typing surface EMG was measured of the trapezius muscle. The subjects were asked to rate sitting comfort and complaints. RESULTS: Although most subjects subjectively preferred the Up-Line, on average no significant differences were found in muscle activity between the two workstations for both patients and healthy subjects. Individually in 5 healthy subjects (25%) and in 6 patients (31%) muscle activity was lower when working at the Up-Line. CONCLUSION: Although some subjects subjectively prefer the Up-Line in sitting comfort, on average the Up-Line did not decrease the muscle activity, both in healthy subjects as in patients with WAD.