A linear force-summing hand dynamometer independent of point of application

Theory, design and construction details are presented for a versatile strain gauge hand dynamometer. What distinguishes this instrument is that sensitivity is completely independent of the location. Force is applied so it is capable of linearly summing forces exerted at multiple locations along the length of the active area of the dynamometer. In addition to including the basic principles of this transducer, a template for the instrument and an accompanying spread sheet is provided for computing transducer response characteristics for instruments of arbitrary size, including sensitivity and force range, depending on particular measurement requirements. Variations of this dynamometer were constructed and used for measuring grip and pinch strength, as well as for measuring submaximal exertions produced during manual activities and tasks. Because this dynamometer is compact and rigid, one of suitable dimensions may be substituted as a handle for tools or objects handled during work for directly measuring applied exertions and grip force. Examples of practical applications of this instrument are given for hand biomechanics, hand tool ergonomics, and clinical evaluations.     

A gap detection tactility test for sensory deficits associated with carpal tunnel syndrome

An automated gap detection tactility test was investigated for quantifying sensory deficits associated with carpal tunnel syndrome (CTS). The test, which involved sensing a tiny gap in an otherwise smooth surface by probing with the finger, had functional resemblance to many work-related tactile activities such as detecting scratches or surface defects. Gap detection thresholds were measured using the converging staircase method of limits paradigm. Sixteen normal subjects between 21 and 66 years of age were tested for studying important factors affecting gap detection thresholds. Actively probing with the index finger had a threshold almost an order of magnitude more sensitive (mean = 0.19 mm, SD = 0.11 mm) than passive touch (mean = 1.63 mm, SD = 0.62 mm), which was similar to two-point discrimination. Average thresholds decreased by 24% as contact force increased from 25 to 75 g. Performance in this tactility test quickly stabilized and showed little learning effects over the period of the test, as evidenced by the lack of significant differences between six replicates. The results were highly repeatable. No significant threshold differences were observed between test and retest trials on different days, or between dominant and non-dominant hands. A contact force of 50 g was recommended as optimal for this test since it required moderate force but resulted in a smaller threshold compared with 25 or 75 g. A companion study was conducted using eight normal subjects and ten subjects diagnosed as having CTS. Average gap detection threshold, when finger probing was allowed, was 0.20 mm (SD = 0.11 min) for the normal subjects and increased two-fold to 0.40 mm (SD = 0.19 mm) for the CTS subjects. Average gap detection threshold, when the finger probing was not allowed, was 1.71 mm (SD = 0.53 mm) for the normal subjects and increased by 48% to 2.53 mm (SD = 0.87 mm) for the CTS subjects. The results suggest that people suffering from CTS may experience similar functional deficits in daily living and work activities. The small inter-subject variability makes this test a candidate for having utility as a monitoring test for loss of cutaneous tactile sensitivity.     

A video-based system for acquiring biomechanical data synchronizedwith arbitrary events and activities

A video-based data acquisition and interactive multimedia data extraction system are described for measuring and synchronizing large quantities of biomechanical analog data with arbitrary events and activities. Analog signals from up to 32 channels are digitized, frequency-shift key (FSK) coded, and recorded directly onto the audio tracks of a video tape in synchronization with the video information. The data acquisition system includes an A/D converter that digitizes up to 16 multiplexed channels of 8-b data at a fixed sample rate between 60 and 960 Hz, and an FSK modem that transfers the data onto one of two VHS high fidelity (20 Hz-20 kHz bandwidth) audio tracks. Twenty megabytes of digitized data and time codes, along with associated video and normal audio are contained on a conventional 120-min video tape. An analyst interactively reviews the video tape off-line using a computer-controlled VCR and identifies specific events that divide arbitrary activities into time segments. The computer automatically extracts the biomechanical data corresponding to each time segment for further processing or analysis. This system is useful for ergonomics, gait analysis, sports medicine, sleep laboratory, biomechanics, or any application where complex visual events are synchronized with low-frequency analog data     

Mental workload during brain-computer interface training

It is not well understood how people perceive the difficulty of performing brain-computer interface (BCI) tasks, which specific aspects of mental workload contribute the most, and whether there is a difference in perceived workload between participants who are able-bodied and disabled. This study evaluated mental workload using the NASA Task Load Index (TLX), a multi-dimensional rating procedure with six subscales: Mental Demands, Physical Demands, Temporal Demands, Performance, Effort, and Frustration. Able-bodied and motor disabled participants completed the survey after performing EEG-based BCI Fitts' law target acquisition and phrase spelling tasks. The NASA-TLX scores were similar for able-bodied and disabled participants. For example, overall workload scores (range 0-100) for 1D horizontal tasks were 48.5 (SD = 17.7) and 46.6 (SD 10.3), respectively. The TLX can be used to inform the design of BCIs that will have greater usability by evaluating subjective workload between BCI tasks, participant groups, and control modalities. PRACTITIONER SUMMARY: Mental workload of brain-computer interfaces (BCI) can be evaluated with the NASA Task Load Index (TLX). The TLX is an effective tool for comparing subjective workload between BCI tasks, participant groups (able-bodied and disabled), and control modalities. The data can inform the design of BCIs that will have greater usability.     

Short-term changes in upper extremity dynamic mechanical response parameters following power hand tool use

Dynamic mechanical response parameters (stiffness, damping and effective mass), physiological properties (strength and swelling) and symptoms of the upper limb were measured before power tool operation, immediately following and 24 h after power tool operation. Tool factors, including peak torque (3 Nm and 9 Nm) and torque build-up time (50 ms and 250 ms), were controlled in a full factorial design. Twenty-nine inexperienced power hand tool users were randomly assigned to one of four conditions and operated a pistol grip nutrunner four times per min for 1 h in the laboratory. Isometric strength decreased immediately following tool use (15%) (p < 0.01) and 24 h later (9%) (p < 0.05). Mechanical parameters of stiffness (p < 0.05) and effective mass (p < 0.05) were affected by build-up time. An average decrease in stiffness (43%) and effective mass (57%) of the upper limb was observed immediately following pistol grip nutrunner operation for the long (250 ms) build-up time. A previously developed biomechanical model was used to estimate handle force and displacement associated with the tool factors in the experiment. The conditions associated with the greatest predicted handle force and displacement had the greatest decrease in mechanical stiffness and effective mass, and the greatest increase in localized discomfort.     

Gain effects on performance using a head-controlled computer input device.

The purpose of this study was to use a Fitts' task to (1) determine how control-display gain influences performance using a head-controlled computer input device; (2) compare relative sensitivity to gain and optimal gain between head control and hand/arm control; and (3) investigate control-display gain interactions with other task factors including target width, movement amplitude and direction. The task was a discrete target acquisition task using circular targets of 2.9 mm, 8.1 mm, and 23.5 mm, movement amplitudes of 24.3 mm and 61.7 mm, and eight radial directions including 0 degrees, 45 degrees, 90 degrees, 135 degrees, 180 degrees, 225 degrees, 270 degrees, and 315 degrees. Each device was operated at four gain levels. Ten subjects participated. The results indicated that gain had a significant effect on movement time for both types of pointing devices and exhibited local minimums. Discrete target acquisition at all gains was aptly described using Fitts' Law for both input devices. The mouse gain resulting in minimum movement time and RMS cursor deviation was between 1.0 and 2.0. The minimum movement time and RMS cursor deviation for the head-controlled pointer occurred at a gain between 0.3 and 0.6. Average movement time at the optimal head-controlled pointer gain had a slope of 169 ms/bit and was more than 76% greater than at the optimal mouse gain with a slope of 135 ms/bit. In addition, average RMS displacement was more than 27% greater for the head-controlled pointer at its optimal gain setting than for the mouse. Gain had the greatest effect for small target widths and long movement amplitudes using the head-controlled pointer. Average movement time increased 37% when increasing the head-controlled pointer gain from 0.6 to 1.2 for the small target width, but only increased 0.3% when increasing gain for the large target width. Average movement time also increased 12% when decreasing the head-controlled pointer gain from 0.3 to 0.15 for the long movement amplitude, but decreased 0.3% when decreasing gain for the short movement amplitude.     

A 16-channel 8-parameter waveform electrotactile stimulation system

We have developed a general-purpose electrotactile (electrocutaneous) stimulation system as a research tool for studying psychophysiological performance associated with various stimulation waveforms. An experimenter-defined command file specifies the stimulation current and waveform of each of the 16 channels. The system provides burst onset delay of 0-20 ms, phase current of 0-50 mA, interphase interval of 0-1000 microseconds, number of pulses per burst from 1-100, pulse repetition rate of 0.1-25 kHz, phase width of 2-1000 microseconds, and functionally-monophasic pulses (with zero dc current) or balanced-biphasic pulses (with equal positive and negative phases). The system automatically delivers the desired stimulation, prompts the subject for responses, and then logs subject responses. Key features of the system are 1) very flexible choice of bursts of pulsatile waveforms, 2) real-time control of all of the waveform parameters as mathematical functions of external analog inputs, and 3) high-performance electrode-driver circuitry.     

Forces associated with pneumatic power screwdriver operation: statics and dynamics

The statics and dynamics of pneumatic power screwdriver operation were investigated in the context of predicting forces acting against the human operator. A static force model is described in the paper, based on tool geometry, mass, orientation in space, feed force, torque build up, and stall torque. Three common power hand tool shapes are considered, including pistol grip, right angle, and in-line. The static model estimates handle force needed to support a power nutrunner when it acts against the tightened fastener with a constant torque. A system of equations for static force and moment equilibrium conditions are established, and the resultant handle force (resolved in orthogonal directions) is calculated in matrix form. A dynamic model is formulated to describe pneumatic motor torque build-up characteristics dependent on threaded fastener joint hardness. Six pneumatic tools were tested to validate the deterministic model. The average torque prediction error was 6.6% (SD = 5.4%) and the average handle force prediction error was 6.7% (SD = 6.4%) for a medium-soft threaded fastener joint. The average torque prediction error was 5.2% (SD = 5.3%) and the average handle force prediction error was 3.6% (SD = 3.2%) for a hard threaded fastener joint. Use of these equations for estimating handle forces based on passive mechanical elements representing the human operator is also described. These models together should be useful for considering tool handle force in the selection and design of power screwdrivers, particularly for minimizing handle forces in the prevention of injuries and work related musculoskeletal disorders.     

A new method for estimating hand internal loads from external force measurements

This study examines using force vectors measured using a directional strain gauge grip dynamometer for estimating finger flexor tendon tension. Fifty-three right-handed participants (25 males and 28 females) grasped varying-sized instrumented cylinders (2.54, 3.81, 5.08, 6.35 and 7.62 cm diameter) using a maximal voluntary power grip. The grip force vector magnitude and direction, referenced to the third metacarpal, was resolved by taking two orthogonal grip force measurements. A simple biomechanical model incorporating the flexor tendons was used to estimate long finger tendon tension during power grip. The flexor digitorum superficialis and the flexor digitorum profundus were assumed to create a moment about the metacarpal phalange (MCP) joint that equals and counteracts a moment around the MCP joint measured externally by the dynamometer. The model revealed that tendon tension increased by 130% from the smallest size handle to the largest, even though grip force magnitude decreased 36% for the same handles. The study demonstrates that grip force vectors may be useful for estimating internal hand forces.