Mobile Phone-Connected Wearable Motion Sensors to Assess Postoperative Mobilization

Abstract

BackgroundEarly mobilization after surgery reduces the incidence of a wide range of complications. Wearable motion sensors measure movements over time and transmit this data wirelessly, which has the potential to monitor patient recovery and encourages patients to engage in their own rehabilitation.ObjectiveWe sought to determine the ability of off-the-shelf activity sensors to remotely monitor patient postoperative mobility.MethodsConsecutive subjects were recruited under the Department of Neurosurgery at Columbia University. Patients were enrolled during physical therapy sessions. The total number of steps counted by the two blinded researchers was compared to the steps recorded on four activity sensors positioned at different body locations.ResultsA total of 148 motion data points were generated. The start time, end time, and duration of each walking session were accurately recorded by the devices and were remotely available for the researchers to analyze. The sensor accuracy was significantly greater when placed over the ankles than over the hips (P<.001). Our multivariate analysis showed that step length was an independent predictor of sensor accuracy. On linear regression, there was a modest positive correlation between increasing step length and increased ankle sensor accuracy (r=.640, r 2=.397) that reached statistical significance on the multivariate model (P=.03). Increased gait speed also correlated with increased ankle sensor accuracy, although less strongly (r=.444, r 2=.197). We did not note an effect of unilateral weakness on the accuracy of left- versus right-sided sensors. Accuracy was also affected by several specific measures of a patient’s level of physical assistance, for which we generated a model to mathematically adjust for systematic underestimation as well as disease severity.ConclusionsWe provide one of the first assessments of the accuracy and utility of widely available and wirelessly connected activity sensors in a postoperative patient population. Our results show that activity sensors are able to provide invaluable information about a patient’s mobility status and can transmit this data wirelessly, although there is a systematic underestimation bias in more debilitated patients.

Human Activity Recognition in AAL Environments Using Random Projections

“…HAR using smartphones or other types of portable or wearable sensor platforms has been used for assessing movement quality after stroke [17], such as upper extremity motion [18], for assessing gait characteristics of human locomotion for rehabilitation and diagnosis of medical conditions [19], for postoperative mobilization [20], for detecting Parkinson's disease, back pain, and hemiparesis [21], for cardiac rehabilitation [22], for physical therapy, for example, if a user is correctly doing the exercises recommended by a physician [23, 24], for detecting abnormal activities arising due to memory loss for dementia care [25, 26], for dealing with Alzheimer's [27] and neurodegenerative diseases such as epilepsy [28], for assessment of physical activity for children and adolescents suffering from hyperlipidaemia, hypertension, cardiovascular disease, and type 2 diabetes [29], for detecting falls [30, 31], for addressing physical inactivity when dealing with obesity [32], for analysing sleeping patterns [33], for estimating energy expenditures of a person to assess his/her healthy daily lifestyle [34], and for recognizing the user's intent in the domain of rehabilitation engineering such as smart walking support systems to assist motor-impaired persons and the elderly [35]. …”

Continuous Digital Assessment for Weight Loss Surgery Patients

“…Only participants with connected Fitbit device data (n = 675) were used in the analysis. Fitbit devices have been found to be valid and reliable for capturing step, heart rate, and sleep data [11][12][13][14]. We restricted the analysis to the time period encompassing 12 weeks (84 days) before to 12 weeks after the participants' reported procedure dates (n = 520).…”

Comprehensive Review on Current and Future Regulatory Requirements on Wearable Sensors in Preclinical and Clinical Testing

“…In motion analysis, wearable devices are used mainly to monitor activity status, which is fundamental in rehabilitation phase, to perform gait analysis and to recognize activities, anomalies and accidents [11,12]. The technology of these devices is usually similar to commercial activity trackers one, based on a compound of sensors: Accelerometers, used to measure accelerations and forces [13][14][15]; magnetometers, designed to understand device orientation; Gyroscopes, which give rotational information.…”