Communicative capital: a key resource for human-machine shared agency and collaborative capacity.

In this work, we present a perspective on the role machine intelligence can play in supporting human abilities. In particular, we consider research in rehabilitation technologies such as prosthetic devices, as this domain requires tight coupling between human and machine. Taking an agent-based view of such devices, we propose that human-machine collaborations have a capacity to perform tasks which is a result of the combined agency of the human and the machine. We introduce communicative capital as a resource developed by a human and a machine working together in ongoing interactions. Development of this resource enables the partnership to eventually perform tasks at a capacity greater than either individual could achieve alone. We then examine the benefits and challenges of increasing the agency of prostheses by surveying literature which demonstrates that building communicative resources enables more complex, task-directed interactions. The viewpoint developed in this article extends current thinking on how best to support the functional use of increasingly complex prostheses, and establishes insight toward creating more fruitful interactions between humans and supportive, assistive, and augmentative technologies.

Development of a Risk Behavior Diagnosis Scale for E-cigarette Use.

Objectives: Adolescent use of electronic cigarettes has risen dramatically, prompting concerns about the health effects. There is need for brief measures to assess adolescents' perceived threat and efficacy related to e-cigarette use and cessation. A 12-item Likert-type scale was modeled after the Risk Behavior Diagnosis Scale and designed to assess threat (ie, severity and susceptibility of threat) and efficacy (ie, self-efficacy and response efficacy) as they relate to e-cigarette use. Methods: The scale was administered online to a developmental sample of 674 adolescents to examine internal consistency and factor structure. Participants (52.1% female, M age = 14.6) were representative of the surrounding community (60% non-Hispanic white; 27% non-Hispanic black; 8% Hispanic). Results: Factor analysis and Velicer's minimum average partial test revealed 2 factors (as expected), which explained 68% of the variance. Analyses revealed strong internal consistency, with Cronbach's alpha of .93 overall and alphas of .92 and .87 for threat and efficacy subscales, respectively. The measure also exhibited good convergent and discriminant validity with other constructs. Conclusions: The measure demonstrates strong preliminary reliability and validity for a developmental sample of adolescents.

Exploring the Impact of Machine-Learned Predictions on Feedback from an Artificial Limb.

Learning to get by without an arm or hand can be very challenging, and existing prostheses do not yet fill the needs of individuals with amputations. One promising solution is to improve the feedback from the device to the user. Towards this end, we present a simple machine learning interface to supplement the control of a robotic limb with feedback to the user about what the limb will be experiencing in the near future. A real-time prediction learner was implemented to predict impact-related electrical load experienced by a robot limb; the learning system's predictions were then communicated to the device's user to aid in their interactions with a workspace. We tested this system with five able-bodied subjects. Each subject manipulated the robot arm while receiving different forms of vibrotactile feedback regarding the arm's contact with its workspace. Our trials showed that using machine-learned predictions as a basis for feedback led to a statistically significant improvement in task performance when compared to purely reactive feedback from the device. Our study therefore contributes initial evidence that prediction learning and machine intelligence can benefit not just control, but also feedback from an artificial limb. We expect that a greater level of acceptance and ownership can be achieved if the prosthesis itself takes an active role in transmitting learned knowledge about its state and its situation of use.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

BACKGROUND: Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. OBJECTIVES: The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). STUDY DESIGN: Case series study. METHODS: We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. RESULTS: Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. CONCLUSION: Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. CLINICAL RELEVANCE: Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses.

An investigation of state population characteristics that moderate the relationship of state seat belt law and use in the United States.

OBJECTIVES: Primary enforcement laws have been shown to be effective methods for increasing seat belt use at the state level. METHOD: This study investigates state differences in the effectiveness of primary enforcement laws by assessing whether a state's academic achievement, health ranking, economic prosperity, violent crime rates, government effectiveness, gender distribution, or proportion of rural roads moderate the relationship between those laws and seat belt compliance rates. RESULTS: Aggregate state-level academic achievement, health ranking, government effectiveness, and proportion of rural roads uniquely moderated the seat belt use differences between primary and secondary enforcement states. CONCLUSIONS: This evidence suggests that cultural, social, and demographic differences among regions may be important factors in explaining state-level differences in the effectiveness of primary enforcement of seat belt laws.

An enclosed in-gel PCR amplification cassette with multi-target, multi-sample detection for platform molecular diagnostics.

This work describes a self-contained, simple, disposable, and inexpensive gel capillary cassette for DNA amplification in near point of care settings. The cassette avoids the need for pumps or valves during raw sample delivery or polymerase chain reaction (PCR) amplification steps. The cassette contains capillary reaction units that can be stored at room temperature for up to 3 months. The current cassette configuration format simultaneously tests up to 16 patients for two or more targets, accommodates different sample types on the same cassette, has integrated positive and negative controls and allows flexibility for multiple geometries. PCR reagents in the cassette are desiccated to allow storage at room temperature with rehydration by raw sample at the time of testing. The sample is introduced to the cassette via a transfer pipette simply by capillary force. DNA amplification was carried out in a portable prototype instrument for PCR thermal cycling with fluorescence detection of amplified products by melt curve analysis (MCA). To demonstrate performance, raw genital swabs and urine were introduced to the same cassette to simultaneously detect four sexually transmitted infections. Herpes Simplex Viruses (HSV-1 and HSV-2) were detected from raw genital swabs. Ureaplasma urealyticum (UU) and Mycoplasma homonis (MH) were detected from raw urine. Results for multiple patients were obtained in as little as 50 min. This platform allows multiparameter clinical testing with a pre-assembled cassette that requires only the introduction of raw sample. Modification of the prototype device to accommodate larger cassettes will ultimately provide high throughput simultaneous testing of even larger numbers of samples for many different targets, as is required for some clinical applications. Combinations of wax and/or polymer cassettes holding capillary reaction units are feasible. The components of the cassette are suited to mass production and robotic assembly to produce a readily manufactured disposable reaction cassette that can be configured for disease-specific testing panels. Rapid testing with a disposable reaction cassette on an inexpensive instrument will enable on the spot evaluation of patients in the clinic for faster medical decision-making and more informed therapeutic choices.

A miniaturized and integrated gel post platform for multiparameter PCR detection of herpes simplex viruses from raw genital swabs.

Herpes simplex virus (HSV) is one of the most prevalent viruses, with acute and recurrent infections in humans. The current gold standard for the diagnosis of HSV is viral culture which takes 2-14 days and has low sensitivity. In contrast, DNA amplification by polymerase chain reaction (PCR) can be performed within 1-2 h. We here describe a multiparameter PCR assay to simultaneously detect HSV-1 and HSV-2 DNA templates, together with integrated positive and negative controls, with product detection by melting curve analysis (MCA), in an array of semi-solid polyacrylamide gel posts. Each gel post is 0.67 µL in volume, and polymerized with all the components required for PCR. Both PCR and MCA can currently be performed in one hour and 20 min. Unprocessed genital swabs collected in universal transport medium were directly added to the reagents before or after polymerization, diffusing from atop the gel posts. The gel post platform detects HSV templates in as little as 2.5 nL of raw sample. In this study, 45 genital swab specimens were tested blindly as a preliminary validation of this platform. The concordance of PCR on gel posts with conventional PCR was 91%. The primer sequestration method introduced here (wherein different primers are placed in different sets of posts) enables the simultaneous detection of multiple pathogens for the same sample, together with positive and negative controls, on a single chip. This platform accepts unprocessed samples and is readily adaptable to detection of multiple different pathogens or biomarkers for point-of-care diagnostics.