Identifying balance impairments in people with Parkinson's disease using video and wearable sensors

BACKGROUND

Falls and near falls are common among people with Parkinson's (PwP). To date, most wearable sensor research focussed on fall detection, few studies explored if wearable sensors can detect instability.

RESEARCH QUESTION

Can instability (caution or near-falls) be detected using wearable sensors in comparison to video analysis?

METHODS

Twenty-four people (aged 60-86) with and without Parkinson's were recruited from community groups. Movements (e.g. walking, turning, transfers and reaching) were observed in the gait laboratory and/or at home; recorded using clinical measures, video and five wearable sensors (attached on the waist, ankles and wrists). After defining 'caution' and 'instability', two researchers evaluated video data and a third the raw wearable sensor data; blinded to each other's evaluations. Agreement between video and sensor data was calculated on stability, timing, step count and strategy.

RESULTS

Data was available for 117 performances: 82 (70%) appeared stable on video. Ratings agreed in 86/117 cases (74%). Highest agreement was noted for chair transfer, timed up and go test and 3 m walks. Video analysts noted caution (slow, contained movements, safety-enhancing postures and concentration) and/or instability (saving reactions, stopping after stumbling or veering) in 40/134 performances (30%): raw wearable sensor data identified 16/35 performances rated cautious or unstable (sensitivity 46%) and 70/82 rated stable (specificity 85%). There was a 54% chance that a performance identified from wearable sensors as cautious/unstable was so; rising to 80% for stable movements.

SIGNIFICANCE

Agreement between wearable sensor and video data suggested that wearable sensors can detect subtle instability and near-falls. Caution and instability were observed in nearly a third of performances, suggesting that simple, mildly challenging actions, with clearly defined start- and end-points, may be most amenable to monitoring during free-living at home. Using the genuine near-falls recorded, work continues to automatically detect subtle instability using algorithms.

Low-cost Kinect Version 2 imaging system for breath hold monitoring and gating: Proof of concept study for breast cancer VMAT radiotherapy

Voluntary inspiration breath hold (VIBH) for left breast cancer patients has been shown to be a safe and effective method of reducing radiation dose to the heart. Currently, VIBH protocol compliance is monitored visually. In this work, we establish whether it is possible to gate the delivery of radiation from an Elekta linac using the Microsoft Kinect version 2 (Kinect v2) depth sensor to measure a patient breathing signal. This would allow contactless monitoring during VMAT treatment, as an alternative to equipment-assisted methods such as active breathing control (ABC). Breathing traces were acquired from six left breast radiotherapy patients during VIBH. We developed a gating interface to an Elekta linac, using the depth signal from a Kinect v2 to control radiation delivery to a programmable motion platform following patient breathing patterns. Radiation dose to a moving phantom with gating was verified using point dose measurements and a Delta4 verification phantom. 60 breathing traces were obtained with an acquisition success rate of 100%. Point dose measurements for gated deliveries to a moving phantom agreed to within 0.5% of ungated delivery to a static phantom using both a conventional and VMAT treatment plan. Dose measurements with the verification phantom showed that there was a median dose difference of better than 0.5% and a mean (3% 3 mm) gamma index of 92.6% for gated deliveries when using static phantom data as a reference. It is possible to use a Kinect v2 device to monitor voluntary breath hold protocol compliance in a cohort of left breast radiotherapy patients. Furthermore, it is possible to use the signal from a Kinect v2 to gate an Elekta linac to deliver radiation only during the peak inhale VIBH phase.

The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery

Consumer‐grade distance sensors, such as the Microsoft Kinect devices (v1 and v2), have been investigated for use as marker‐free motion monitoring systems for radiotherapy. The radiotherapy delivery environment is challenging for such sensors because of the proximity to electromagnetic interference (EMI) from the pulse forming network which fires the magnetron and electron gun of a linear accelerator (linac) during radiation delivery, as well as the requirement to operate them from the control area. This work investigated whether using Kinect v2 sensors as motion monitors was feasible during radiation delivery. Three sensors were used each with a 12 m USB 3.0 active cable which replaced the supplied 3 m USB 3.0 cable. Distance output data from the Kinect v2 sensors was recorded under four conditions of linac operation: (i) powered up only, (ii) pulse forming network operating with no radiation, (iii) pulse repetition frequency varied between 6 Hz and 400 Hz, (iv) dose rate varied between 50 and 1450 monitor units (MU) per minute. A solid water block was used as an object and imaged when static, moved in a set of steps from 0.6 m to 2.0 m from the sensor and moving dynamically in two sinusoidal‐like trajectories. Few additional image artifacts were observed and there was no impact on the tracking of the motion patterns (root mean squared accuracy of 1.4 and 1.1 mm, respectively). The sensors’ distance accuracy varied by 2.0 to 3.8 mm (1.2 to 1.4 mm post distance calibration) across the range measured; the precision was 1 mm. There was minimal effect from the EMI on the distance calibration data: 0 mm or 1 mm reported distance change (2 mm maximum change at one position). Kinect v2 sensors operated with 12 m USB 3.0 active cables appear robust to the radiotherapy treatment environment.

PACS number(s): 87.53 JW, 87.55 N‐, 87.63 L‐