Monitoring Functional Capability of Individuals with Lower Limb Amputations Using Mobile Phones

To be effective, a prescribed prosthetic device must match the functional requirements and capabilities of each patient. These capabilities are usually assessed by a clinician and reported by the Medicare K-level designation of mobility. However, it is not clear how the K-level designation objectively relates to the use of prostheses outside of a clinical environment. Here, we quantify participant activity using mobile phones and relate activity measured during real world activity to the assigned K-levels. We observe a correlation between K-level and the proportion of moderate to high activity over the course of a week. This relationship suggests that accelerometry-based technologies such as mobile phones can be used to evaluate real world activity for mobility assessment. Quantifying everyday activity promises to improve assessment of real world prosthesis use, leading to a better matching of prostheses to individuals and enabling better evaluations of future prosthetic devices.Max Nader Center for Rehabilitation Technologies and Outcome

Fall Classification by Machine Learning Using Mobile Phones

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls–left and right lateral, forward trips, and backward slips–while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls

Comparative effectiveness of manipulation, mobilisation and the Activator instrument in treatment of non-specific neck pain: a systematic review

BACKGROUND: Neck pain is a common problem and different forms of manual therapy are used in its treatment. The purpose of this systematic review was to critically appraise the literature that directly compared manipulation, mobilisation and the Activator instrument for non-specific neck pain. METHODS: Electronic databases (MEDLINE, MANTIS and CINAHL) were searched from their inception to October 2005 for all English language randomised clinical trials that directly compared manipulation, mobilisation and the Activator instrument. Inclusion and exclusion criteria were applied to select the studies and these studies were then evaluated using validated criteria. RESULTS: Five such studies were identified. The methodological quality was mostly poor. Findings from the studies were mixed and no one therapy was shown to be more effective than the others. CONCLUSION: Further high quality research has to be done before a recommendation can be made as to the most effective manual method for non-specific neck pain

Relative effectiveness and adverse effects of cervical manipulation, mobilisation and the activator instrument in patients with sub-acute non-specific neck pain: results from a stopped randomised trial

<p>Abstract</p> <p>Background</p> <p>Neck pain of a mechanical nature is a common complaint seen by practitioners of manual medicine, who use a multitude of methods to treat the condition. It is not known, however, if any of these methods are superior in treatment effectiveness. This trial was stopped due to poor recruitment. The purposes of this report are (1) to describe the trial protocol, (2) to report on the data obtained from subjects who completed the study, (3) to discuss the problems we encountered in conducting this study.</p> <p>Methods</p> <p>A pragmatic randomised clinical trial was undertaken. Patients who met eligibility criteria were randomised into three groups. One group was treated using specific segmental high velocity low amplitude manipulation (diversified), another by specific segmental mobilisation, and a third group by the Activator instrument. All three groups were also treated for any myofascial distortions and given appropriate exercises and advice. Participants were treated six times over a three-week period or until they reported being pain free. The primary outcome measure for the study was Patient Global Impression of Change (PGIC); secondary outcome measures included the Short-Form Health Survey (SF-36v₂), the neck Bournemouth Questionnaire, and the numerical rating scale for pain intensity. Participants also kept a diary of any pain medication taken and noted any perceived adverse effects of treatment. Outcomes were measured at four points: end of treatment, and 3, 6, and 12 months thereafter.</p> <p>Results</p> <p>Between January 2007 and March 2008, 123 patients were assessed for eligibility, of these 47 were considered eligible, of which 16 were allocated to manipulation, 16 to the Activator instrument and 15 to the mobilisation group. Comparison between the groups on the PGIC adjusted for baseline covariants did not show a significant difference for any of the endpoints. Within group analyses for change from baseline to the 12-month follow up for secondary outcomes were significant for all groups on the Bournemouth Questionnaire and for pain, while the mobilisation group had a significant improvement on the PCS and MCS subscales of the SF-36_v2. Finally, there were no moderate, severe, or long-lasting adverse effects reported by any participant in any group.</p> <p>Conclusions</p> <p>Although the small sample size must be taken into consideration, it appears that all three methods of treating mechanical neck pain had a long-term benefit for subacute neck pain, without moderate or serious adverse events associated with any of the treatment methods. There were difficulties in recruiting subjects to this trial. This pragmatic trial should be repeated with a larger sample size.</p

The column density distribution function at z = 0 from HI selected galaxies

We have measured the column density distribution function, f(N HI), at z = 0 using 21-cm HI emission from galaxies selected from a blind HI survey. f(NHI) is found to be smaller and flatter at z = 0 than indicated by high-redshift measurements of damped Lyman alpha (DLA) systems, consistent with the predictions of hierarchical galaxy formation. The derived DLA number density per unit redshift, dNDLA/dz =0.058, is in moderate agreement with values calculated from low-redshift QSO absorption line studies. We use two different methods to determine the types of galaxies which contribute most to the DLA cross-section: comparing the power-law slope of f(NHI) to theoretical predictions and analysing contributions to dNDLA/dz. We find that comparison of the power-law slope cannot rule out spiral discs as the dominant galaxy type responsible for DLA systems. Analysis of dNDLA/dz however, is much more discriminating. We find that galaxies with log MHI< 9.0 make up 34 per cent of dN DLA/dz; Irregular and Magellanic types contribute 25 per cent; galaxies with surface brightness -&#956;25 > 24 mag arcsec-2 account for 22 per cent and sub-L* galaxies contribute 45 per cent to dNDLA/dz. We conclude that a large range of galaxy types give rise to DLA systems, not just large spiral galaxies as previously speculated

The effects of bending speed on the lumbo-pelvic kinematics and movement pattern during forward bending in people with and without low back pain

2016-2017 > Academic research: refereed > Publication in refereed journalbcrcVersion of RecordSelf-fundedPublishe

A new method for determining lumbar spine motion using Bayesian belief network

A Bayesian network dynamic model was developed to determine the kinematics of the intervertebral joints of the lumbar spine. Radiographic images in flexion and extension postures were used as input data for modeling, together with movement information from the skin surface using an electromagnetic motion tracking system. Intervertebral joint movements were then estimated by the graphic network. The validity of the model was tested by comparing the predicted position of the vertebrae in the neutral position with those obtained from the radiographic image in the neutral posture. The correlation between the measured and predicted movements was 0.99 (p < 0.01) with a mean error of less than 1.5°. The movement sequence of the various vertebrae was examined based on the model output, and wide variations in the kinematic patterns were observed. The technique is non-invasive and has potential to be used clinically to measure the kinematics of lumbar intervertebral movement

Trunk posture monitoring with inertial sensors

Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the radiography, photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. This study introduced a method of using a posture monitoring system in estimating the spinal curvature changes during trunk movements on the sagittal and coronal planes and providing trunk posture monitoring during daily activities. The system consisted of three sensor modules, each with one tri-axial accelerometer and three uni-axial gyroscopes orthogonally aligned, and a digital data acquisition and feedback system. The accuracy of this system was tested with a motion analysis system (Vicon 370) in calibration with experimental setup and in trunk posture measurement with nine human subjects, and the performance of the posture monitoring system during daily activities with two human subjects was reported. The averaged root mean squared differences between the measurements of the system and motion analysis system were found to be <1.5° in dynamic calibration, and <3.1° for the sagittal plane and ≤2.1° for the coronal plane in estimation of the trunk posture change during trunk movements. The measurements of the system and the motion analysis system was highly correlated (>0.999 for dynamic calibration and >0.829 for estimation of spinal curvature change in domain planes of movement during flexion and lateral bending). With the sensing modules located on the upper trunk, mid-trunk and the pelvic levels, the inclination of trunk segment and the change of spinal curvature in trunk movements could be estimated. The posture information of five subjects was recorded at 30 s intervals during daily activity over a period of 3 days and 2 h a day. The preliminary results demonstrated that the subjects could improve their posture when feedback signals were provided. The posture monitoring system could be used for the purpose of posture monitoring during daily activity