A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease

Ambulatory Parkinson’s Disease Monitoring (APDM) is both the name of the system as well as the company. The analysis software is called the Mobility Lab. The system comes with a Clinical Data Management System (CDMS) called Mobility Exchange.

It is a watch-sized device consisting of up to six sensors (including an accelerometer, gyroscope and magnetometer) and hold a charge for over 16 h. It enables the registration of different outcomes such as, postural sway - ISway (velocity, frequency, distance), lower limb gait (cadence, stride length, stride velocity, gait cycle time), postural transitions (number of steps, duration, step time), upper limb gait and trunk (trunk range of motion) measures.

The software has several modules such as iSway and iTUG (instrumented Timed Up and Go test). The iTUG test enables the assessment of different parameters in all sub-tasks of the test: (1) sit to stand (duration, peak velocity and trunk range of motion); (2) gait (stride length, stride velocity, cadence gait cycle time, and double support) and trunk movements; (3) turning (number of steps, peak velocity and step time); and (4) Turn to sit (peak turn velocity and trunk range of motion).

In a study with 12 people with PD and 12 controls the iTUG measures were correlated with the UPDRS-III (Unified Parkinson’s Disease Rating Scale–motor part) (r =–0.73, p = 0.006). The iTUG test was shown to be sensitive to untreated PD and to potentially detect progression of PD and response to symptomatic treatments [6].

These proprieties were also studied in two separate studies with two groups of subjects. In study I [7] sensitivity and experimental concurrent validity were assessed by testing 13 subjects with early, untreated PD and 12 age-matched control subjects in the laboratory comparing sway from force-plate CoP (center of pressure) and inertial sensors. In study II [8], test-retest reliability and clinical concurrent validity were assessed by testing 17 early-to-moderate treated PD, and 17 age-matched control subjects in a clinical setting, comparing clinical balance tests with sway from inertial sensors [8].

Regarding concurrent validity, most ACC measures of sway were significantly correlated with CoP measures of sway. Only two measures, mean velocity and mean frequency, were not significantly correlated with CoP. Several ACC measures showed significant correlation with the PIGD (postural instability and gait disability) sub-score of the UPDRS III. All except mean frequency, power and JERK were significantly and positively correlated with the PIGD sub-score related to clinical postural instability. No significant correlations were found between ACC measures and the total UPDRS-III.

The iTUG showed a significant difference in cadence between early PD and control subjects, as well as in angular velocity of arm-swing, turning duration and time to perform turn-to-sits [9].

To characterize posture control in PD, the most sensitive, reliable, and valid ISway measures that are recommend, are: 1) JERK, 2) RMS amplitude and mean velocity from the time-domain measures, and 3) centroidal frequency [8]. Among the subcomponents of iTUG, gait, turning and turn-to-sit were the most reliable and sit-to-stand was the least reliable [9].

Physilog is an ambulatory analysis method that uses body-attached gyroscopes to assess spatio-temporal parameters of gait, sway, physical activity, tremor and bradykinesia. Depending on the expected outcomes, one to seven inertial sensors, including accelerometer and gyroscopes, are used. Minimal attachment sites are used and no calibration is needed.

Gait measurements using this device were performed in 10 people with PD with deep brain stimulation (DBS) [10]. PD patients had significantly different gait parameters compared to controls. Some of the gait parameters had high correlation with UPDRS subscores including stride length with a significant correlation (r = − 0.90) with UPDRS gait subscore. This algorithm was able to detect gait cycles and related gait events with very high sensitivity (>96 %) and with positive prediction value (PPV) > 98 %. The relative error in estimation of the gait cycle time was 2 % and for stride length and stride velocity < 8 %. These results have been demonstrated to be accurate enough to show significant differences between Stimulation ON and Stimulation OFF states in PD patients.

This system had a very high sensitivity in detecting gait cycles (100 % for controls and 100 % for PD patients during Stimulation ON and 99.6 % during Stimulation OFF). Sensitivity in detecting gait events was also very high (99.6 % for controls and 99.3 % for PD patients during Stimulation ON and 96.4 % during Stimulation OFF). The PPV in the detection of gait cycles was 100 % for controls, 98.9 % for Stimulation ON, and 98.4 for the Stimulation OFF group.

In another study [11], a novel symbol based symmetry index was calculated from this inertial sensor data. These measures were used to determine the symmetry of both upper and lower limbs during walking of 11 early-to-mid-stage PD patients and 15 controls. Sensitivity and specificity were high with an area under the curve (ROC) of 0.872 and also showed an excellent ICC of 0.949.

Additionally, algorithms to detect and quantify tremor, and quantify bradykinesia have been proposed and validated using the Physilog. One clinical study included 10 PD patients and 10 control subjects who undertook a 45 min protocol of 17 typical daily activities. The algorithm for tremor detection showed an overall sensitivity of 99.5 % and a specificity of 94.2 % in comparison to a video reference. The estimated tremor amplitude was highly correlated with the Unified Parkinson’s Disease Rating Scale (UPDRS) tremor subscore. There was a high and significant correlation between the estimated bradykinesia-related parameters estimated for the whole period of measurement and respective UPDRS subscores. Another clinical study assessed free movements of upper extremities of 11 PD patients for periods of 3 to 5 h. Correlations similar to those in the the first study were obtained. Moreover, one of the bradykinesia-related parameters showed significant correlation to UPDRS with window sizes as short as 5 min. This study showed that objective, accurate and simultaneous assessment of tremor and bradykinesia can be achieved in free movements of PD patients during their daily activities [12].

The system has been shown to successfully estimate gait parameters with a high degree of accuracy. The method has also been validated to assess gait changes in PD since the results obtained with these instrumental method reliably correlate with clinical scores obtained with commonly used scales, such as the UPDRS [10].

Regarding physical activity, kinematic features of the trunk movements were calculated during the transitions between sitting and standing postures. The proposed method showed a high sensitivity and specificity for the detection of basic body posture allocations: sitting, standing, lying, and walking periods, in PD patients and healthy individuals. Significant differences in parameters were found related to sit-to-stand and stand-to-sit transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. The method was shown to provide a simple, accurate, and effective means to objectively quantifying physical activities in both healthy subjects and PD patients, and possibility useful to assessing the level of motor functions in the latter [13].

The StepWatch 3 (SAM) is a step activity monitor used to capture differences in ambulatory activity according to age and functional limitation. The SAM is the size of a pager and attaches to the ankle. Once applied, it requires no maintenance by the user. The SAM is a microprocessor-linked unit that combines acceleration, position, and timing information to count complete gait cycles. The monitor records stride counts in 1-min intervals synchronized to a 24-h clock and stored on flash memory within the monitor. Stride counts are recorded as 0 during periods of inactivity. During activity the number of counts recorded per 1-min interval varies, depending primarily on the locomotor task characteristics.

Average daily values can be calculated for a number of steps, minutes of activity, number of activity bouts, variability of minute-to-minute activity, and randomness of minute-to-minute activity fluctuations.

The validity, reliability and sensitivity of the SAM are supported by previous research in various diagnostic groups, and at different motor tasks including monitoring of walking and capture ambulatory activity decline in PD [14‐17].

Step activity monitoring data has been shown to be useful for detecting differences in ambulatory activity according to age and functional limitation.

The TriTrac RT3 accelerometer is a triaxial accelerometer that may be suitable for sustained tracking of free-living physical activity in the home environment. It is small, capable of collecting and storing data in one-minute epochs for 21 days, and has no external controls that can be manipulated during data collection.

The accelerometer reliably measured physical activity (ICC, 0.85; 95 % confidence interval, 0.74–0.91). The standard error of measurement indicated that a second test would differ from a baseline test by ±23 %. Mean daily data collected in the first three days differed significantly from that of the mean daily data collected over seven days. The TriTrac RT3 appeared to distinguish level of mobility better than the seven-day recall questionnaire, and participants found the TriTrac RT3 to be a user-friendly and acceptable measure of physical activity [18].

The triaxial accelerometer was found to distinguish between people with PD with different levels of mobility. It was also well tolerated by participants.

The DynaPort MiniMod Hybrid (The Hague, Netherlands; 87 × 45 × 14 mm, 74 g) combines acceleration sensors (range and resolution of ± 2 g and 0.001 g, respectively) and gyroscopes (range and resolution of ± 100 deg/s and 0.0069 deg/s, respectively), with six channels that assess the individual’s movement at 100Hz each. Using a widely available Bluetooth protocol, the DynaPort MiniMod Hybrid communicates wirelessly with a host Personal Computer.

Quantity measures included the total number of walking bouts, the percent of time spent walking which reflects the total walking in relation to the overall walking and non-walking activity, the total number of steps, median walking bout duration, median number of steps, and median cadence per bout. Quality-related sensor-derived measures included: frequency-derived measures that reflect variability of the gait pattern, regularity measures that reflect gait rhythmicity and consistency and the harmonic ratio, which is an index of gait smoothness. In addition, the study performed step-to-step analyses to evaluate the Phase Coordination Index, which is a measure of the consistency and accuracy of the left-right bilateral coordination during walking, i.e., timing of one foot with respect to the other [19].

An algorithm was developed and successfully identified misstep events with a good hit ratio and specificity (odds ratio was 1.84, 95 % confidence intervals: 1.15–2.93) [20]. When applied to the three-day recording, misstep detections were associated with fall status and further supported the validity of the algorithm. The algorithms were able to detect even walking performed at relatively low speeds.

Weiss et. al. [19] demonstrated that PD fallers and non-fallers differ in their gait quality when evaluated in everyday settings, and Iluz et. al. [21] showed that PD fallers tend to produce about 23 % more missteps compare to the non-fallers.

The DynaPort MiniMod Hybrid can detect missteps during activities of daily living among patients with PD. The device is capable of measuring both acceleration and angular velocity in three planes and quantifying several mobility subtasks. It can be used clinically to monitor and promote physical activity [19].

The body-fixed sensors worn for three days can also be used to evaluate fall risk in patients with PD as they perform activities in their home and community settings.

The Axivity (AX3) is a three-axis accelerometer that has a non-volatile flash memory chip linked by a USB-enabled microcontroller. Inside the sealed polycarbonate puck is a temperature sensor, ambient light sensor, and real time clock and lithium polymer battery. The sensor can record up to 21 days of continuous data. The device is suitable for use in a variety of environments and is water resistant (up to 1.5 m).

Comparing data collected over seven days with data collected in the laboratory during scripted tests showed that data collected from gait in free-living conditions can discriminate disease better than laboratory- based data.

Axivity (AX3) was used in a study of 30 people with PD and 30 healthy age-matched controls; 14 gait characteristics were quantified. Of the 14 gait characteristics compared, agreement between instruments was excellent for 4 (ICCs 0.913–0.983); moderate for 4 (ICCs 0.508–0.766); and poor for 6 characteristics (ICCs −0.637–0.370). Further analysis revealed that differences reflect an increased sensitivity of accelerometry in detecting motion, rather than measurement error. The increased sensitivity shown for these characteristics may be of particular interest to researchers wanting to obtain and interpret free world gait data [22].

In a pilot study, 14 body-worn monitor-based outcomes were presented across the gait subdomains, which include magnitude, frequency and spatio-temporal characteristics. Body-worn monitor outcomes were compared with manually recorded values, no significant differences were reported between locomotion and TUG tasks. Significant differences were found for the total distance walked during endurance and times for repeated sit-to-stand-to-sit transitions. These findings supported the feasibility of this method in enhancing measurement of physical capacity, making its application useful in a range of intervention-based studies or pathological assessments [23].

Importantly, it was shown that fallers tended to walk in shorter bouts and had a less variable walking pattern compared to non-fallers. People with PD spent less time walking, took fewer steps, and accumulated proportionally more steps in shorter bouts compared to the elderly, regardless of falls history. Preliminary results showed that there is an association between falls history and physical activity [22].

Use of a body-worn monitor is recommended for the measurement of gait. It is likely to produce more sensitive data for asymmetry and variability features. These results support the use of a single accelerometer-based sensor to assess falls risk in free living settings and to potentially predict falls.

Device description and outcomes that can be measured

Nintendo Wii Balance Board (WBB) is a commonly used accessory for the Wii video game consoles. WBB is considered a cheap, widespread, clinimetric robust device that can be used to measure postural instability in PD patients. It consists of a ground platform, which has four pressure sensors that analyze force distribution and measure CoP movement. It has a small usable area, which can limit to some extent postural assessment in individuals with wider upright stance, and the sensors’ accuracy weight is limited to 150 kg.

The use of WBB has been proposed as an assessment tool for postural instability in PD patients. Additionally, some rehabilitation programs using the WBB addressing balance impairment have been studied with promising results [24].

Clinimetric properties

Test-retest reliability was high (ICCs > 0.75) for CoP path length in 3/4 balance tasks (single limb, eyes open: ICC = 0.86; single limb, eyes closed: ICC = 0.81; double limb, eyes open: ICC = 0.66 and double limb, eyes closed: ICC = 0.91), [25].

Concurrent validity (between WBB and AMTI Model) was excellent in balance tasks and also among test sessions with ICC ranging from 0.77 to 0.89 [25]. In a more recent study [26] with 20 PD patients, the values of ICC were higher (ICC = 0.92-0.98) due to signal processing improvement.

Sensitivity to change of the WBB was considered high, with standard error measurement (SEM) between 8.7–13.1 % and minimum detectable change (MDC) ranging from 24.5–29.4 %. However, WBB yielded higher values for SEM and MDC than a laboratory force plate in 3 out of 4 trials (8.7–13.1 % for the WBB versus 5.3–13.2 % for the Force Plate concerning the SEM values, and 24.5–29.4 % for the WBB versus 14.5–34.7 % for the Force Plate in regard to the MDC values) [25].

Recommendation

WBB is considered a cheap, widespread, clinimetric robust device that can be used to measure postural instability in patients with PD. WBB is recommend for home monitoring of PD patients’ signs. However, some limitations can be identified such as the small usable area, which can limit postural assessment in individuals with wider upright stance, and the sensors’ accuracy weight limit.

Device description and outcomes that can be measured

The GAITRite® system is an electronic pathway that contains pressure sensitive sensors arranged in a grid-like pattern. There are several versions of the GAITRite® device available with different lengths. The carpet is portable and can be rolled up for transportation. It is used for laboratory evaluation and provides information regarding several gait parameters, such as walking speed, cadence and step length. It has been used to assess the degree of axial bradykinesia and the effect of L-dopa therapy on gait variables in PD [27]. Some safety precautions have been highlighted as needed, such as a wall fixed side rail or supervised gait.

Clinimetric properties

Test-retest reliability on 31 older healthy people was assessed in two sessions with a two-week interval. The ICCs were high for walking speed, cadence, step length and left toe in/out angle (between 0.82 and 0.91), and moderate for base of support (0.49 for the left and 0.56 for the right) [28]. Coefficient of variation was small for speed, cadence and step length (3.1–3.5 %), but relatively large for base of support (14.3–15.2 %) and toe in/out angles (24.4–33.0 %) [28].

The relation between GAITRite®-derived gait variables and UPDRS scores and timed tests regarding therapeutic efficiency was examined in 13 patients with PD [27]. Significant correlations were found between L-dopa improvement in gait parameters and the UPDRS III score in the following variables: velocity, stride length, swing phase ratio, and stance phase ratio and double support ratio [27].

Using GAITRite® and self-report questionnaires in a population of 241 elderly healthy individuals, preliminary recommended parameters for clinical meaningful change are 0.001 s for stance time and swing time and 0.25 cm for step length SD [29].

Importantly, we highlight that these clinimetric proprieties refer to the standard GAITRite® walkway and should not be extrapolated to other lengths of this instrument.

Recommendation

The GAITRite® system is a reliable instrument, with extended validation for bradykinesia and the therapeutic effect of L-dopa. Further analysis of sensitivity to change parameters is needed to strengthen its clinimetric properties. Nonetheless, GAITRite® fulfills the proposed criteria and is considered “recommended” for monitoring PD motor signs.

Device description and outcomes that can be measured

Kinesia™ integrates accelerometers and gyroscopes in a compact patient-worn unit to capture kinematic movement disorder features. The sensor component of the device is mounted on a ring, which fits on a finger. The sensor component conveys signal data by wire to a wrist-mounted component, which wirelessly transmits data to a local Computer. The Kinesia™ device has a range limited to 30 m for wireless coverage.

The Kinesia™ system successfully demonstrated the capacity to ascertain tremor with increased time resolution, which could aid in evaluating the efficacy of treatment protocols and improve patient management. Importantly, 45 % of the subject group indicated they would prefer not to wear the device in public.

Clinimetric properties

In one study [30], individuals with PD performed the tremor subset of the UPDRS III while wearing Kinesia™. Quantitative kinematic features were processed and highly correlated to clinician scores for rest tremor (r ⁽²⁾ = 0.89), postural tremor (r ⁽²⁾ = 0.90), and kinetic tremor (r ⁽²⁾ = 0.69). The quantitative features were used to develop a mathematical model that predicted tremor severity scores for new data with low errors [30].

Recommendation

The Kinesia™ sensor component is a small, wrist-mounted component that is able to convey data wirelessly to a local PC with up to 30 m of wireless coverage. The device has been shown to be able to successfully ascertain tremor. However, it suffered from poor subject acceptability.