Canine pedometer & gait kinematics for veterinary monitoring.
Immediately prior to my PhD I worked on a couple of projects in partnership with VetSens - a company local to Newcastle-Upon-Tyne exploring the utility of accelerometers in the assessment of gait of quadruped companion animals.
The first of these was the GaitKeeper System (Ladha et al., 2017). Gaitkeeper was conceived as a quantitative tool to be used during veterinary gait assessment that was more both more affordable and practical than the current gold standard of force plates and/or manual or computer-vision based video coding. Such systems are ubiquitous in human movement research and are seeing increased use in equine veterinary research and practice. Mimicking this prior work, particularly that performed with horses, and to accurately assess the relative acceleration and impact of each leg, sensors were attached directly to the 4 limbs (above the carpal joints of the thoracic limbs and below the tarsal joints of the pelvic limbs). The data collected in this way, following the signal processing methodology outlined in the paper, allowed for the detection of gait features (such contact times), and was robust to size differences across diverse breeds and conformations. The Gaitkeeper system, and by extension similar accelerometer-based methods, shows promise as a future tool in the identification of clinically relevant gait abnormalities in dogs. With further validation, and considering the clinical ubiquity of similar systems in human medicine, a refined Gaitkeeper system could provide vital insight into aspects of canine gait currently difficult to quantify without expensive or impractical insturmentation.
The second of these projects (Ladha et al., 2018) took a different approach for the objective measurement of canine gait features. Instead of individual step or stride events per foot (as with Gaitkeeper) it focussed on the detection of overall step numbers and resulting distance travelled using a collar mounted sensor. Collar-based pedometers like this are common in the marketplace but often use "closed-source" or black-box algorithms that are inaccessible to researchers. The method outlined in the paper addresses the idiosyncracies of canine gait and is entirely open-source. The resulting measures of step count and distance may be advantageous for the use in physical activity detection and classification, or in the "dead-reckoning" of locomotion paths where GPS signals are obscured (such as inside buildings) or battery longevity is a concern (as GPS is battery intensive).
Pedometer signal processing flow diagram.
References
2018
A step in the right direction: an open-design pedometer algorithm for dogs
Cassim Ladha , Zoe Belshaw , Jack O’Sullivan , and 1 more author
Background: Accelerometer-based technologies could be useful in providing objective measures of canine ambulation, but most are either not tailored to the idiosyncrasies of canine gait, or, use un-validated or closed source approaches. The aim of this paper was to validate algorithms which could be applied to accelerometer data for i) counting the number of steps and ii) distance travelled by a dog. To count steps, an approach based on partitioning acceleration was used. This was applied to accelerometer data from 13 dogs which were walked a set distance and filmed. Each footfall captured on video was annotated. In a second experiment, an approach based on signal features was used to estimate distance travelled. This was applied to accelerometer data from 10 dogs with osteoarthritis during normal walks with their owners where GPS (Global Positioning System) was also captured. Pearson’s correlations and Bland Altman statistics were used to compare i) the number of steps measured on video footage and predicted by the algorithm and ii) the distance travelled estimated by GPS and predicted by the algorithm. Results: Both step count and distance travelled could be estimated accurately by the algorithms presented in this paper: 4695 steps were annotated from the video and the pedometer was able to detect 91%. GPS logged a total of 20,184 m meters across all dogs; the mean difference between the predicted and GPS estimated walk length was 211 m and the mean similarity was 79%. Conclusions: The algorithms described show promise in detecting number of steps and distance travelled from an accelerometer. The approach for detecting steps might be advantageous to methods which estimate gross activity because these include energy output from stationary activities. The approach for estimating distance might be suited to replacing GPS in indoor environments or others with limited satellite signal. The algorithms also allow for temporal and spatial components of ambulation to be calculated. Temporal and spatial aspects of dog ambulation are clinical indicators which could be used for diagnosis or monitoring of certain diseases, or used to provide information in support of canine weight-loss programmes.
@article{ladha2018step,title={A step in the right direction: an open-design pedometer algorithm for dogs},author={Ladha, Cassim and Belshaw, Zoe and O’Sullivan, Jack and Asher, Lucy},journal={BMC veterinary research},volume={14},number={1},pages={1--10},year={2018},publisher={BioMed Central},doi={10.1186/s12917-018-1422-3},url={https://doi.org/10.1186/s12917-018-1422-3},dimensions={true},}
2017
GaitKeeper: a system for measuring canine gait
Cassim Ladha , Jack O’Sullivan , Zoe Belshaw , and 1 more author
It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs’ gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias. This means reliable, early detection of canine gait abnormalities is challenging, which may have detrimental implications for dogs’ welfare. In this paper, we draw from approaches and technologies used in human movement science and describe a system for objectively measuring temporal gait characteristics in dogs (step-time, swing-time, stance-time). Asymmetries and variabilities in these characteristics are of known clinical significance when assessing lameness but presently may only be assessed on coarse scales or under highly instrumented environments. The system consists an inertial measurement unit, containing a 3-axis accelerometer and gyroscope coupled with a standardized walking course. The measurement unit is attached to each leg of the dog under assessment before it is walked around the course. The data by the measurement unit is then processed to identify steps and subsequently, micro-gait characteristics. This method has been tested on a cohort of 19 healthy dogs of various breeds ranging in height from 34.2 cm to 84.9 cm. We report the system as capable of making precise step delineations with detections of initial and final contact times of foot-to-floor to a mean precision of 0.011 s and 0.048 s, respectively. Results are based on analysis of 12,678 foot falls and we report a sensitivity, positive predictive value and F-score of 0.81, 0.83 and 0.82 respectively. To investigate the effect of gait on system performance, the approach was tested in both walking and trotting with no significant performance deviation with 7249 steps reported for a walking gait and 4977 for a trotting gait. The number of steps reported for each leg were approximately equal and this consistency was true in both walking and trotting gaits. In the walking gait 1965, 1790, 1726 and 1768 steps were reported for the front left, front right, hind left and hind right legs respectively. 1361, 1250, 1176 and 1190 steps were reported for each of the four legs in the trotting gait. The proposed system is a pragmatic and precise solution for obtaining objective measurements of canine gait. With further development, it promises potential for a wide range of applications in both research and clinical practice.
@article{ladha2017gaitkeeper,title={GaitKeeper: a system for measuring canine gait},author={Ladha, Cassim and O’Sullivan, Jack and Belshaw, Zoe and Asher, Lucy},journal={Sensors},volume={17},number={2},pages={309},year={2017},publisher={MDPI},doi={10.3390/s17020309},url={https://doi.org/10.3390/s17020309},dimensions={true},}
