Gait is the walking pattern of an individual which is unique to every person and an abnormality in the gait may be a sign of underlying medical conditions such as Parkinson’s, Heart diseases, spinal injuries and spinal stenosis.
Spinal stenosis is a condition which afflicts older adults above 70 years of age and is caused due to the narrowing of the spinal canal leading to compression of the nerve roots resulting in back pain, leg pain, weakness and paraesthesia in lower limbs and can severely affect the gait of older adults. The most common cause is due to wear-and-tear changes in the spine related to osteoarthritis.
Singapore-based healthcare startup Healint has developed a medical app – Walk buddy to monitor gait in patients with spinal stenosis. They used the accelerometer embedded in smartphones to monitor the walking capability of spinal stenosis patients using this mobile app. They hypothesized that people with difficulties in walking would have different accelerometer signals.
Till now the functional capacity of patients suffering from spinal stenosis used to be assessed using the six-minute walk test (6MWT). However it had limitations such as the lack of reference data for different age groups that could be used in the clinical evaluation of the disease. They showed that, using smartphones to monitor patients could be a more convenient and affordable method for long-term monitoring in an outpatient setting.
The study was conducted on ten patients afflicted with varying degrees of back pain caused by spinal stenosis at the spinal clinic in Khoo Teck Puat Hospital (KTPH, Singapore). Three healthy patients acted as controls. Each participant was asked to walk back and forth at his comfortable speed on a 20-meter walkway for 3 minutes. A smartphone (Samsung S4 phone) installed with the Walk Buddy application was inserted in the participant’s pant pocket, which gathered the acceleration data at 50 Hz.
The signals generated by the accelerometer during walking was recorded and the number of steps and distance covered in 3 minutes were recorded by the Walk Buddy app. In total, data of 22 walking sessions from the 13 participants were generated. This raw data was smoothed using a third -order Butterworth filter with a cut-off value of 5Hz.
The results confirmed their hypothesis that people with difficulties in walking will present different accelerometer signals. The acceleration of the healthy participant had a greater magnitude than that of the patient and the walking steps were clearly apparent in the healthy participant compared to the patients afflicted with spinal stenosis. This shows that the accelerometric data could indeed be used to analyze human walking gait.
Earlier methods included using isolated accelerometer units to assess walking gait parameters when the user is walking on a treadmill or overground. However, the need for regular calibration and the need to be properly attached to the upper body of the user limited its usage on a daily basis. Walk buddy, uses the embedded accelerometer in Smartphones and with some proper and simple pre-processing techniques could be used to affectively assess the gait of the users.
This is the first time such a study has been conducted on patients with lumbar spinal stenosis. Their App was compatible with other smartphone models too with consistent accelerometer data generated across various brands, indicating the broad applicability of their approach. Their approach was suitable for daily use and cost-effective too, with the smartphone just placed loosely in a user’s pant pocket.
Current methods of assessment and treatment of spinal stenosis involve verbal assessment by the doctor and a walk test, which could in future be replaced by this App. Since it can detect a variety of parameters such as exact steps, distance, stops and speed accurately along with characteristics of the walk such as balance of the walk, stance and contacts of the foot to the ground; it can help monitor the patients both in and out of the clinical settings.
They envisage that with more work, this application could eventually be used to assess a number of other diseases such as stroke, Parkinson disease, multiple sclerosis, brain trauma and COPD too.
Healint is a startup which is making healthcare monitoring ubiquitous using the most readily available technology today–smart phones! Their Migraine tracking and reporting app, Migraine Buddy quickly became the number one migraine tracking app on Google Play when it was launched. This new App could be a boon to care-givers and physicians and can also help keep track of the patient’s progress.