Justin B. Rowe

The manumeter: a wearable device for monitoring daily use of the wrist and fingers.

Nonobtrusive options for monitoring the wrist and hand movement are needed for stroke rehabilitation and other applications. This paper describes the “manumeter,” a device that logs total angular distance travelled by wrist and finger joints using a magnetic ring worn on the index finger and two triaxial magnetometers mounted in a watch-like unit. We describe an approach to estimate the wrist and finger joint angles using a radial basis function network that maps differential magnetometer readings to joint angles. We tested this approach by comparing manumeter estimates of total angular excursion with those from a passive goniometric exoskeleton worn simultaneously as seven participants completed a set of 12 manual tasks at low-, medium-, and high-intensity conditions on a first testing day, 1-2 days later, and 6-8 days later, using only the original calibration from the first testing day. Manumeter estimates scaled proportionally to the intensity of hand activity. Estimates of angular excursion made with the manumeter were 92.5% ± 28.4 (SD), 98.3% ± 23.3, and 94.7% ± 19.3 of the goniometric exoskeleton across the three testing days, respectively. Magnetic sensing of wrist and finger movement is nonobtrusive and can quantify the amount of use of the hand across days.

The Manumeter: A non-obtrusive wearable device for monitoring spontaneous use of the wrist and fingers

This paper describes the design and pilot testing of a novel device for unobtrusive monitoring of wrist and hand movement through a sensorized watch and a magnetic ring system called the manumeter. The device senses the magnetic field of the ring through two triaxial magnetometers and records the data to onboard memory which can be analyzed later by connecting the watch unit to a computer. Wrist and finger joint angles are estimated using a radial basis function network. We compared joint angle estimates collected using the manumeter to direct measurements taken using a passive exoskeleton and found that after a 60 minute trial, 95% of the radial/ulnar deviation, wrist flexion/extension and finger flexion/extension estimates were within 2.4, 5.8, and 4.7 degrees of their actual values respectively. The device measured angular distance traveled for these three joints within 10.4%, 4.5%, and 14.3 % of their actual values. The manumeter has potential to improve monitoring of real world use of the hand after stroke and in other applications.

Robot-assisted Guitar Hero for finger rehabilitation after stroke

This paper describes the design and testing of a robotic device for finger therapy after stroke: FINGER (Finger Individuating Grasp Exercise Robot). FINGER makes use of stacked single degree-of-freedom mechanisms to assist subjects in moving individual fingers in a naturalistic grasping pattern through much of their full range of motion. The device has a high bandwidth of control (-3dB at approximately 8 Hz) and is backdriveable. These characteristics make it capable of assisting in grasping tasks that require precise timing. We therefore used FINGER to assist individuals with a stroke (n= 8) and without impairment (n= 4) in playing a game similar to Guitar Hero©. The subjects attempted to move their fingers to target positions at times specified by notes that were graphically streamed to popular music. We show here that by automatically adjusting the robot gains, it is possible to use FINGER to modulate the subjects success rate at the game, across a range of impairment levels. Modulating success rates did not alter the stroke subjects effort, although the unimpaired subjects exerted more force when they were made less successful. We also present a novel measure of finger individuation that can be assessed as individuals play Guitar Hero with FINGER. The results demonstrate the ability of FINGER to provide controlled levels of assistance during an engaging computer game, and to quantify finger individuation after stroke.

The variable relationship between arm and hand use: A rationale for using finger magnetometry to complement wrist accelerometry when measuring daily use of the upper extremity

Wrist-worn accelerometers are becoming more prevalent as a means to assess use of the impaired upper extremity in daily life after stroke. However, wrist accelerometry does not measure joint movements of the hand, which are integral to functional use of the upper extremity. In this study, we used a custom-built, non-obtrusive device called the manumeter to measure both arm use (via wrist accelerometry) and hand use (via finger magnetometry) of a group of unimpaired subjects while they performed twelve motor tasks at three intensities. We also gave the devices to four stroke subjects and asked them to wear them for six hours a day for one month. From the in-lab testing we found that arm use was a strong predictor of hand use for individual tasks, but that the slope of the relationship varied by up to a factor of ~12 depending on the task being performed. Consistent with this, in the daily use data collected from stroke subjects we found a broad spread in the relationship between arm and hand use. These results suggest that analyzing the spread of the relationship between daily hand and arm use will give more insight into upper extremity recovery than wrist accelerometry or finger magnetometry alone, because the spread reflects the nature of the daily tasks performed as well as the amount of upper extremity use.

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial

Background. Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning. Objective. To determine the therapeutic effects of high and low levels of robotic assistance during finger training. Methods. We designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions. Results. Both groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)—particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training. Conclusions. Robot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.